Merge pull request #5224 from amd-jnovotny/dlf-matt-docs643

Deep learning frameworks edits for scale (#5189)

.azuredevops/ci-builds/aomp-mainline.yml

@@ -1,42 +0,0 @@
-variables:
-- group: common
-- template: /.azuredevops/variables-global.yml
-
-resources:
-  repositories:
-  - repository: aomp_repo
-    type: github
-    endpoint: ROCm
-    name: ROCm/aomp
-    ref: amd-mainline
-  - repository: aomp-extras_repo
-    type: github
-    endpoint: ROCm
-    name: ROCm/aomp-extras
-    ref: amd-mainline
-  - repository: flang_repo
-    type: github
-    endpoint: ROCm
-    name: ROCm/flang
-    ref: amd-mainline
-  - repository: llvm-project_repo
-    type: github
-    endpoint: ROCm
-    name: ROCm/llvm-project
-    ref: amd-mainline
-  pipelines:
-  - pipeline: rocr-runtime_pipeline
-    source: \ROCR-Runtime
-    trigger:
-      branches:
-        include:
-        - amd-mainline
-# this job will only be triggered after successful build sequence of llvm-project and ROCR-Runtime
-
-trigger: none
-pr: none
-
-jobs:
-  - template: ${{ variables.CI_COMPONENT_PATH }}/aomp.yml
-    parameters:
-      checkoutRepo: aomp_repo

.azuredevops/components/AMDMIGraphX.yml

@@ -1,10 +1,29 @@
 parameters:
+- name: componentName
+  type: string
+  default: AMDMIGraphX
 - name: checkoutRepo
   type: string
   default: 'self'
 - name: checkoutRef
   type: string
   default: ''
+# monorepo related parameters
+# - name: sparseCheckoutDir
+#   type: string
+#   default: ''
+- name: triggerDownstreamJobs
+  type: boolean
+  default: false
+- name: downstreamAggregateNames
+  type: string
+  default: ''
+- name: buildDependsOn
+  type: object
+  default: null
+- name: unifiedBuild
+  type: boolean
+  default: false
 # set to true if doing full build of ROCm stack
 # and dependencies are pulled from same pipeline
 - name: aggregatePipeline
@@ -93,7 +112,11 @@ parameters:
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: AMDMIGraphX_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
+    ${{ if parameters.buildDependsOn }}:
+      dependsOn:
+        - ${{ each build in parameters.buildDependsOn }}:
+          - ${{ build }}_ubuntu2204_${{ job.target }}
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -121,6 +144,8 @@ jobs:
         dependencyList: ${{ parameters.rocmDependencies }}
         gpuTarget: ${{ job.target }}
         aggregatePipeline: ${{ parameters.aggregatePipeline }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
       parameters:
         extraBuildFlags: >-
@@ -146,12 +171,12 @@ jobs:
         gpuTarget: ${{ job.target }}
 
 - ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: AMDMIGraphX_test_${{ job.target }}
-    dependsOn: AMDMIGraphX_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_test_ubuntu2204_${{ job.target }}
+    dependsOn: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
     condition:
       and(succeeded(),
         eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
-        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), variables['Build.DefinitionName'])),
+        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), '${{ parameters.componentName }}')),
         eq(${{ parameters.aggregatePipeline }}, False)
       )
     variables:
@@ -183,6 +208,8 @@ jobs:
         checkoutRef: ${{ parameters.checkoutRef }}
         dependencyList: ${{ parameters.rocmTestDependencies }}
         gpuTarget: ${{ job.target }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
     - task: CMake@1
       displayName: MIGraphXTest CMake Flags
       inputs:
@@ -199,7 +226,7 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/gpu-diagnostics.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
       parameters:
-        componentName: AMDMIGraphX
+        componentName: ${{ parameters.componentName }}
         testExecutable: make
         testParameters: -j$(nproc) check
         testPublishResults: false

.azuredevops/components/MIOpen.yml

@@ -1,10 +1,29 @@
 parameters:
+- name: componentName
+  type: string
+  default: MIOpen
 - name: checkoutRepo
   type: string
   default: 'self'
 - name: checkoutRef
   type: string
   default: ''
+# monorepo related parameters
+- name: sparseCheckoutDir
+  type: string
+  default: ''
+- name: triggerDownstreamJobs
+  type: boolean
+  default: false
+- name: downstreamAggregateNames
+  type: string
+  default: ''
+- name: buildDependsOn
+  type: object
+  default: null
+- name: unifiedBuild
+  type: boolean
+  default: false
 # set to true if doing full build of ROCm stack
 # and dependencies are pulled from same pipeline
 - name: aggregatePipeline
@@ -74,10 +93,31 @@ parameters:
         target: gfx942
       - gfx90a:
         target: gfx90a
+- name: downstreamComponentMatrix
+  type: object
+  default:
+    - MIVisionX:
+      name: MIVisionX
+      checkoutRepo: mivisionx_repo
+      sparseCheckoutDir: ''
+      skipUnifiedBuild: 'false'
+      buildDependsOn:
+        - MIOpen_build
+    - AMDMIGraphX:
+      name: AMDMIGraphX
+      checkoutRepo: amdmigraphx_repo
+      sparseCheckoutDir: ''
+      skipUnifiedBuild: 'false'
+      buildDependsOn:
+        - MIOpen_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: MIOpen_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
+    ${{ if parameters.buildDependsOn }}:
+      dependsOn:
+        - ${{ each build in parameters.buildDependsOn }}:
+          - ${{ build }}_ubuntu2204_${{ job.target }}
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -95,6 +135,7 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
       parameters:
         checkoutRepo: ${{ parameters.checkoutRepo }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/miopen-get-ck-build.yml
       parameters:
         gpuTarget: ${{ job.target }}
@@ -104,11 +145,13 @@ jobs:
         dependencyList: ${{ parameters.rocmDependencies }}
         gpuTarget: ${{ job.target }}
         aggregatePipeline: ${{ parameters.aggregatePipeline }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
     - task: Bash@3
       displayName: Build and install other dependencies
       inputs:
         targetType: inline
-        workingDirectory: $(Build.SourcesDirectory)
+        workingDirectory: $(Agent.BuildDirectory)/s
         script: |
           sed -i '/composable_kernel/d' requirements.txt
           mkdir -p $(Agent.BuildDirectory)/miopen-deps
@@ -130,8 +173,10 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
       parameters:
         gpuTarget: ${{ job.target }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
       parameters:
+        componentName: ${{ parameters.componentName }}
         gpuTarget: ${{ job.target }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
@@ -143,9 +188,9 @@ jobs:
           - miopen-deps
 
 - ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: MIOpen_test_${{ job.target }}
+  - job: ${{ parameters.componentName }}_test_ubuntu2204_${{ job.target }}
     timeoutInMinutes: 180
-    dependsOn: MIOpen_build_${{ job.target }}
+    dependsOn: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
     condition:
       and(succeeded(),
         eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
@@ -169,6 +214,7 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
       parameters:
         checkoutRepo: ${{ parameters.checkoutRepo }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/miopen-get-ck-build.yml
       parameters:
@@ -178,11 +224,13 @@ jobs:
         checkoutRef: ${{ parameters.checkoutRef }}
         dependencyList: ${{ parameters.rocmTestDependencies }}
         gpuTarget: ${{ job.target }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
     - task: Bash@3
       displayName: Build and install other dependencies
       inputs:
         targetType: inline
-        workingDirectory: $(Build.SourcesDirectory)
+        workingDirectory: $(Agent.BuildDirectory)/s
         script: |
           sed -i '/composable_kernel/d' requirements.txt
           mkdir -p $(Agent.BuildDirectory)/miopen-deps
@@ -193,7 +241,7 @@ jobs:
       displayName: 'MIOpen Test CMake Flags'
       inputs:
         cmakeArgs: >-
-          -DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm;$(Build.SourcesDirectory)/bin;$(Agent.BuildDirectory)/miopen-deps
+          -DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm;$(Agent.BuildDirectory)/s/bin;$(Agent.BuildDirectory)/miopen-deps
           -DCMAKE_INSTALL_PREFIX=$(Agent.BuildDirectory)/rocm
           -DCMAKE_CXX_COMPILER=$(Agent.BuildDirectory)/rocm/llvm/bin/amdclang++
           -DCMAKE_C_COMPILER=$(Agent.BuildDirectory)/rocm/llvm/bin/amdclang
@@ -203,19 +251,19 @@ jobs:
           -DBUILD_DEV=OFF
           -DMIOPEN_USE_MLIR=ON
           -DMIOPEN_GPU_SYNC=OFF
-          ..
+          $(Agent.BuildDirectory)/s
     - task: Bash@3
       displayName: 'MIOpen Test Build'
       inputs:
         targetType: inline
+        workingDirectory: build
         script: |
           cmake --build . --target tests -- -j$(nproc)
-        workingDirectory: $(Build.SourcesDirectory)/build
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/gpu-diagnostics.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
       parameters:
-        componentName: MIOpen
-        testParameters: '--output-on-failure --force-new-ctest-process --output-junit test_output.xml --exclude-regex "test_rnn_seq_api|GPU_Conv2dTuningAsm_FP32"'
+        componentName: ${{ parameters.componentName }}
+        testParameters: '--output-on-failure --force-new-ctest-process --output-junit test_output.xml --exclude-regex "test_rnn_seq_api|GPU_Conv2dTuningAsm_FP32|GPU_Conv2dTuningAsmBwdWrw_FP32"'
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
       parameters:
         aptPackages: ${{ parameters.aptPackages }}
@@ -224,3 +272,15 @@ jobs:
         gpuTarget: ${{ job.target }}
         extraCopyDirectories:
           - miopen-deps
+
+# - ${{ if parameters.triggerDownstreamJobs }}:
+#   - ${{ each component in parameters.downstreamComponentMatrix }}:
+#     - ${{ if not(and(parameters.unifiedBuild, eq(component.skipUnifiedBuild, 'true'))) }}:
+#       - template: /.azuredevops/components/${{ component.name }}.yml@pipelines_repo
+#         parameters:
+#           checkoutRepo: ${{ component.checkoutRepo }}
+#           # sparseCheckoutDir: ${{ component.sparseCheckoutDir }}
+#           buildDependsOn: ${{ component.buildDependsOn }}
+#           downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ parameters.componentName }}
+#           triggerDownstreamJobs: true
+#           unifiedBuild: ${{ parameters.unifiedBuild }}

.azuredevops/components/MIVisionX.yml

@@ -1,10 +1,29 @@
 parameters:
+- name: componentName
+  type: string
+  default: MIVisionX
 - name: checkoutRepo
   type: string
   default: 'self'
 - name: checkoutRef
   type: string
   default: ''
+# monorepo related parameters
+# - name: sparseCheckoutDir
+#   type: string
+#   default: ''
+- name: triggerDownstreamJobs
+  type: boolean
+  default: false
+- name: downstreamAggregateNames
+  type: string
+  default: ''
+- name: buildDependsOn
+  type: object
+  default: null
+- name: unifiedBuild
+  type: boolean
+  default: false
 # set to true if doing full build of ROCm stack
 # and dependencies are pulled from same pipeline
 - name: aggregatePipeline
@@ -60,6 +79,7 @@ parameters:
 - name: rocmTestDependencies
   type: object
   default:
+    - aomp
     - clr
     - half
     - hipBLAS-common
@@ -88,7 +108,11 @@ parameters:
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: MIVisionX_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
+    ${{ if parameters.buildDependsOn }}:
+      dependsOn:
+        - ${{ each build in parameters.buildDependsOn }}:
+          - ${{ build }}_ubuntu2204_${{ job.target }}
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -110,6 +134,8 @@ jobs:
         dependencyList: ${{ parameters.rocmDependencies }}
         gpuTarget: ${{ job.target }}
         aggregatePipeline: ${{ parameters.aggregatePipeline }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
       parameters:
         extraBuildFlags: >-
@@ -131,12 +157,12 @@ jobs:
     #     gpuTarget: ${{ job.target }}
 
 - ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: MIVisionX_test_${{ job.target }}
-    dependsOn: MIVisionX_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_test_ubuntu2204_${{ job.target }}
+    dependsOn: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
     condition:
       and(succeeded(),
         eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
-        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), variables['Build.DefinitionName'])),
+        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), '${{ parameters.componentName }}')),
         eq(${{ parameters.aggregatePipeline }}, False)
       )
     variables:
@@ -161,6 +187,8 @@ jobs:
         checkoutRef: ${{ parameters.checkoutRef }}
         dependencyList: ${{ parameters.rocmTestDependencies }}
         gpuTarget: ${{ job.target }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
     - task: Bash@3
       displayName: Build MIVisionX tests
       inputs:
@@ -174,7 +202,7 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/gpu-diagnostics.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
       parameters:
-        componentName: MIVisionX
+        componentName: ${{ parameters.componentName }}
         testDir: 'mivisionx-tests'
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
       parameters:

.azuredevops/components/ROCR-Runtime.yml

@@ -28,8 +28,8 @@ parameters:
 - name: rocmTestDependencies
   type: object
   default:
+    - amdsmi
     - llvm-project
-    - rocm_smi_lib
     - rocprofiler-register
 
 - name: jobMatrix
@@ -111,14 +111,6 @@ jobs:
       parameters:
         aptPackages: ${{ parameters.aptPackages }}
         packageManager: ${{ job.packageManager }}
-    - task: Bash@3
-      displayName: Install libhwloc5
-      inputs:
-        targetType: 'inline'
-        script: |
-          wget http://ftp.us.debian.org/debian/pool/main/h/hwloc/libhwloc5_1.11.12-3_amd64.deb
-          wget http://ftp.us.debian.org/debian/pool/main/h/hwloc/libhwloc-dev_1.11.12-3_amd64.deb
-          sudo apt install -y --allow-downgrades ./libhwloc5_1.11.12-3_amd64.deb ./libhwloc-dev_1.11.12-3_amd64.deb
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
       parameters:
@@ -161,6 +153,10 @@ jobs:
         targetType: 'inline'
         workingDirectory: $(Build.SourcesDirectory)/rocrtst/suites/test_common
         script: |
+          echo $(Build.SourcesDirectory)/rocrtst/thirdparty/lib | sudo tee -a /etc/ld.so.conf.d/rocm-ci.conf
+          sudo cat /etc/ld.so.conf.d/rocm-ci.conf
+          sudo ldconfig -v
+          ldconfig -p
           if [ -e /opt/rh/gcc-toolset-14/enable ]; then
             source /opt/rh/gcc-toolset-14/enable
           fi

.azuredevops/components/hipBLAS.yml

@@ -1,10 +1,29 @@
 parameters:
+- name: componentName
+  type: string
+  default: hipBLAS
 - name: checkoutRepo
   type: string
   default: 'self'
 - name: checkoutRef
   type: string
   default: ''
+# monorepo related parameters
+- name: sparseCheckoutDir
+  type: string
+  default: ''
+- name: triggerDownstreamJobs
+  type: boolean
+  default: false
+- name: downstreamAggregateNames
+  type: string
+  default: ''
+- name: buildDependsOn
+  type: object
+  default: null
+- name: unifiedBuild
+  type: boolean
+  default: false
 # set to true if doing full build of ROCm stack
 # and dependencies are pulled from same pipeline
 - name: aggregatePipeline
@@ -69,10 +88,30 @@ parameters:
         target: gfx942
       - gfx90a:
         target: gfx90a
+# MIOpen depends on both rocRAND and hipBLAS
+# for a unified build, hipBLAS will be the one to call MIOpen
+- name: downstreamComponentMatrix
+  type: object
+  default:
+    - MIOpen:
+      name: MIOpen
+      sparseCheckoutDir: projects/miopen
+      skipUnifiedBuild: 'false'
+      buildDependsOn:
+        - hipBLAS_build
+      unifiedBuild:
+        downstreamAggregateNames: hipBLAS+rocRAND
+        buildDependsOn:
+          - hipBLAS_build
+          - rocRAND_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: hipBLAS_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
+    ${{ if parameters.buildDependsOn }}:
+      dependsOn:
+        - ${{ each build in parameters.buildDependsOn }}:
+          - ${{ build }}_ubuntu2204_${{ job.target }}
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -88,6 +127,7 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
       parameters:
         checkoutRepo: ${{ parameters.checkoutRepo }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aocl.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
       parameters:
@@ -95,6 +135,8 @@ jobs:
         dependencyList: ${{ parameters.rocmDependencies }}
         gpuTarget: ${{ job.target }}
         aggregatePipeline: ${{ parameters.aggregatePipeline }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
       parameters:
         extraBuildFlags: >-
@@ -109,9 +151,12 @@ jobs:
           -GNinja
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
       parameters:
+        componentName: ${{ parameters.componentName }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
         gpuTarget: ${{ job.target }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
       parameters:
+        componentName: ${{ parameters.componentName }}
         gpuTarget: ${{ job.target }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
@@ -121,46 +166,67 @@ jobs:
         installAOCL: true
         gpuTarget: ${{ job.target }}
 
-- ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: hipBLAS_test_${{ job.target }}
-    dependsOn: hipBLAS_build_${{ job.target }}
-    condition:
-      and(succeeded(),
-        eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
-        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), variables['Build.DefinitionName'])),
-        eq(${{ parameters.aggregatePipeline }}, False)
-      )
-    variables:
-    - group: common
-    - template: /.azuredevops/variables-global.yml
-    pool: ${{ job.target }}_test_pool
-    workspace:
-      clean: all
-    steps:
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
-      parameters:
-        aptPackages: ${{ parameters.aptPackages }}
-        pipModules: ${{ parameters.pipModules }}
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
-      parameters:
-        gpuTarget: ${{ job.target }}
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
-      parameters:
-        checkoutRef: ${{ parameters.checkoutRef }}
-        dependencyList: ${{ parameters.rocmTestDependencies }}
-        gpuTarget: ${{ job.target }}
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/gpu-diagnostics.yml
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
-      parameters:
-        componentName: hipBLAS
-        testExecutable: $(Agent.BuildDirectory)/rocm/bin/hipblas-test
-        testParameters: '--yaml hipblas_smoke.yaml --gtest_output=xml:./test_output.xml --gtest_color=yes'
-        testDir: '$(Agent.BuildDirectory)/rocm/bin'
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
-      parameters:
-        aptPackages: ${{ parameters.aptPackages }}
-        pipModules: ${{ parameters.pipModules }}
-        environment: test
-        gpuTarget: ${{ job.target }}
+- ${{ if eq(parameters.unifiedBuild, False) }}:
+  - ${{ each job in parameters.jobMatrix.testJobs }}:
+    - job: ${{ parameters.componentName }}_test_ubuntu2204_${{ job.target }}
+      dependsOn: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
+      condition:
+        and(succeeded(),
+          eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
+          not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), '${{ parameters.componentName }}')),
+          eq(${{ parameters.aggregatePipeline }}, False)
+        )
+      variables:
+      - group: common
+      - template: /.azuredevops/variables-global.yml
+      pool: ${{ job.target }}_test_pool
+      workspace:
+        clean: all
+      steps:
+      - checkout: none
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
+        parameters:
+          aptPackages: ${{ parameters.aptPackages }}
+          pipModules: ${{ parameters.pipModules }}
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
+        parameters:
+          preTargetFilter: ${{ parameters.componentName }}
+          gpuTarget: ${{ job.target }}
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
+        parameters:
+          checkoutRef: ${{ parameters.checkoutRef }}
+          dependencyList: ${{ parameters.rocmTestDependencies }}
+          gpuTarget: ${{ job.target }}
+          ${{ if parameters.triggerDownstreamJobs }}:
+            downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/gpu-diagnostics.yml
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
+        parameters:
+          componentName: ${{ parameters.componentName }}
+          testExecutable: $(Agent.BuildDirectory)/rocm/bin/hipblas-test
+          testParameters: '--yaml hipblas_smoke.yaml --gtest_output=xml:./test_output.xml --gtest_color=yes'
+          testDir: '$(Agent.BuildDirectory)/rocm/bin'
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
+        parameters:
+          aptPackages: ${{ parameters.aptPackages }}
+          pipModules: ${{ parameters.pipModules }}
+          environment: test
+          gpuTarget: ${{ job.target }}
+
+- ${{ if parameters.triggerDownstreamJobs }}:
+  - ${{ each component in parameters.downstreamComponentMatrix }}:
+    - ${{ if not(and(parameters.unifiedBuild, eq(component.skipUnifiedBuild, 'true'))) }}:
+      - template: /.azuredevops/components/${{ component.name }}.yml@pipelines_repo
+        parameters:
+          checkoutRepo: ${{ parameters.checkoutRepo }}
+          sparseCheckoutDir: ${{ component.sparseCheckoutDir }}
+          triggerDownstreamJobs: true
+          unifiedBuild: ${{ parameters.unifiedBuild }}
+          ${{ if parameters.unifiedBuild }}:
+            buildDependsOn: ${{ component.unifiedBuild.buildDependsOn }}
+            downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ component.unifiedBuild.downstreamAggregateNames }}
+          ${{ else }}:
+            buildDependsOn: ${{ component.buildDependsOn }}
+            downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ parameters.componentName }}

.azuredevops/components/hipFFT.yml

@@ -80,11 +80,11 @@ parameters:
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: ${{ parameters.componentName }}_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
     ${{ if parameters.buildDependsOn }}:
       dependsOn:
         - ${{ each build in parameters.buildDependsOn }}:
-          - ${{ build }}_${{ job.target }} # todo: add OS
+          - ${{ build }}_ubuntu2204_${{ job.target }}
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -141,12 +141,12 @@ jobs:
     #     gpuTarget: ${{ job.target }}
 
 - ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: ${{ parameters.componentName }}_test_${{ job.target }}
-    dependsOn: ${{ parameters.componentName }}_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_test_ubuntu2204_${{ job.target }}
+    dependsOn: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
     condition:
       and(succeeded(),
         eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
-        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), variables['Build.DefinitionName'])),
+        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), '${{ parameters.componentName }}')),
         eq(${{ parameters.aggregatePipeline }}, False)
       )
     variables:

.azuredevops/components/hipRAND.yml

@@ -72,15 +72,15 @@ parameters:
     testJobs:
       - { os: ubuntu2204, packageManager: apt, target: gfx942 }
       - { os: ubuntu2204, packageManager: apt, target: gfx90a }
-# - name: downstreamComponentMatrix
-#   type: object
-#   default:
-#     - rocFFT:
-#       name: rocFFT
-#       sparseCheckoutDir: projects/rocfft
-#       skipUnifiedBuild: 'false'
-#       buildDependsOn:
-#         - hipRAND_build
+- name: downstreamComponentMatrix
+  type: object
+  default:
+    - rocFFT:
+      name: rocFFT
+      sparseCheckoutDir: projects/rocfft
+      skipUnifiedBuild: 'false'
+      buildDependsOn:
+        - hipRAND_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
@@ -206,14 +206,14 @@ jobs:
           environment: test
           gpuTarget: ${{ job.target }}
 
-# - ${{ if parameters.triggerDownstreamJobs }}:
-#   - ${{ each component in parameters.downstreamComponentMatrix }}:
-#     - ${{ if not(and(parameters.unifiedBuild, eq(component.skipUnifiedBuild, 'true'))) }}:
-#       - template: /.azuredevops/components/${{ component.name }}.yml@pipelines_repo
-#         parameters:
-#           checkoutRepo: ${{ parameters.checkoutRepo }}
-#           sparseCheckoutDir: ${{ component.sparseCheckoutDir }}
-#           buildDependsOn: ${{ component.buildDependsOn }}
-#           downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ parameters.componentName }}
-#           triggerDownstreamJobs: true
-#           unifiedBuild: ${{ parameters.unifiedBuild }}
+- ${{ if parameters.triggerDownstreamJobs }}:
+  - ${{ each component in parameters.downstreamComponentMatrix }}:
+    - ${{ if not(and(parameters.unifiedBuild, eq(component.skipUnifiedBuild, 'true'))) }}:
+      - template: /.azuredevops/components/${{ component.name }}.yml@pipelines_repo
+        parameters:
+          checkoutRepo: ${{ parameters.checkoutRepo }}
+          sparseCheckoutDir: ${{ component.sparseCheckoutDir }}
+          buildDependsOn: ${{ component.buildDependsOn }}
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ parameters.componentName }}
+          triggerDownstreamJobs: true
+          unifiedBuild: ${{ parameters.unifiedBuild }}

.azuredevops/components/hipSOLVER.yml

@@ -1,10 +1,29 @@
 parameters:
+- name: componentName
+  type: string
+  default: hipSOLVER
 - name: checkoutRepo
   type: string
   default: 'self'
 - name: checkoutRef
   type: string
   default: ''
+# monorepo related parameters
+- name: sparseCheckoutDir
+  type: string
+  default: ''
+- name: triggerDownstreamJobs
+  type: boolean
+  default: false
+- name: downstreamAggregateNames
+  type: string
+  default: ''
+- name: buildDependsOn
+  type: object
+  default: null
+- name: unifiedBuild
+  type: boolean
+  default: false
 # set to true if doing full build of ROCm stack
 # and dependencies are pulled from same pipeline
 - name: aggregatePipeline
@@ -66,7 +85,11 @@ parameters:
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: hipSOLVER_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
+    ${{ if parameters.buildDependsOn }}:
+      dependsOn:
+        - ${{ each build in parameters.buildDependsOn }}:
+          - ${{ build }}_ubuntu2204_${{ job.target }}
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -81,18 +104,21 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
       parameters:
         checkoutRepo: ${{ parameters.checkoutRepo }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
       parameters:
         checkoutRef: ${{ parameters.checkoutRef }}
         dependencyList: ${{ parameters.rocmDependencies }}
         gpuTarget: ${{ job.target }}
         aggregatePipeline: ${{ parameters.aggregatePipeline }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
   # build external gtest and lapack
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
       parameters:
         componentName: external
-        cmakeBuildDir: '$(Build.SourcesDirectory)/deps/build'
-        cmakeSourceDir: '$(Build.SourcesDirectory)/deps'
+        cmakeBuildDir: '$(Agent.BuildDirectory)/s/deps/build'
+        cmakeSourceDir: '$(Agent.BuildDirectory)/s/deps'
         installDir: '$(Pipeline.Workspace)/deps-install'
         extraBuildFlags: >-
           -DBUILD_BOOST=OFF
@@ -111,8 +137,10 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
       parameters:
         gpuTarget: ${{ job.target }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
       parameters:
+        componentName: ${{ parameters.componentName }}
         gpuTarget: ${{ job.target }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
     # - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
@@ -122,44 +150,49 @@ jobs:
     #     extraCopyDirectories:
     #       - deps-install
 
-- ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: hipSOLVER_test_${{ job.target }}
-    dependsOn: hipSOLVER_build_${{ job.target }}
-    condition:
-      and(succeeded(),
-        eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
-        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), variables['Build.DefinitionName'])),
-        eq(${{ parameters.aggregatePipeline }}, False)
-      )
-    variables:
-    - group: common
-    - template: /.azuredevops/variables-global.yml
-    pool: ${{ job.target }}_test_pool
-    workspace:
-      clean: all
-    steps:
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
-      parameters:
-        aptPackages: ${{ parameters.aptPackages }}
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
-      parameters:
-        gpuTarget: ${{ job.target }}
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
-      parameters:
-        checkoutRef: ${{ parameters.checkoutRef }}
-        dependencyList: ${{ parameters.rocmTestDependencies }}
-        gpuTarget: ${{ job.target }}
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/gpu-diagnostics.yml
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
-      parameters:
-        componentName: hipSOLVER
-        testDir: '$(Agent.BuildDirectory)/rocm/bin'
-        testExecutable: './hipsolver-test'
-        testParameters: '--gtest_filter="*checkin*" --gtest_output=xml:./test_output.xml --gtest_color=yes'
-    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
-      parameters:
-        aptPackages: ${{ parameters.aptPackages }}
-        environment: test
-        gpuTarget: ${{ job.target }}
+- ${{ if eq(parameters.unifiedBuild, False) }}:
+  - ${{ each job in parameters.jobMatrix.testJobs }}:
+    - job: ${{ parameters.componentName }}_test_ubuntu2204_${{ job.target }}
+      dependsOn: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
+      condition:
+        and(succeeded(),
+          eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
+          not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), '${{ parameters.componentName }}')),
+          eq(${{ parameters.aggregatePipeline }}, False)
+        )
+      variables:
+      - group: common
+      - template: /.azuredevops/variables-global.yml
+      pool: ${{ job.target }}_test_pool
+      workspace:
+        clean: all
+      steps:
+      - checkout: none
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
+        parameters:
+          aptPackages: ${{ parameters.aptPackages }}
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
+        parameters:
+          preTargetFilter: ${{ parameters.componentName }}
+          gpuTarget: ${{ job.target }}
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
+        parameters:
+          checkoutRef: ${{ parameters.checkoutRef }}
+          dependencyList: ${{ parameters.rocmTestDependencies }}
+          gpuTarget: ${{ job.target }}
+          ${{ if parameters.triggerDownstreamJobs }}:
+            downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/gpu-diagnostics.yml
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
+        parameters:
+          componentName: ${{ parameters.componentName }}
+          testDir: '$(Agent.BuildDirectory)/rocm/bin'
+          testExecutable: './hipsolver-test'
+          testParameters: '--gtest_filter="*checkin*" --gtest_output=xml:./test_output.xml --gtest_color=yes'
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
+        parameters:
+          aptPackages: ${{ parameters.aptPackages }}
+          environment: test
+          gpuTarget: ${{ job.target }}

.azuredevops/components/rocBLAS.yml

@@ -104,17 +104,17 @@ parameters:
         - rocBLAS_build
     # rocSOLVER depends on both rocBLAS and rocPRIM
     # for a unified build, rocBLAS will be the one to call rocSOLVER
-    # - rocSOLVER:
-    #   name: rocSOLVER
-    #   sparseCheckoutDir: projects/rocsolver
-    #   skipUnifiedBuild: 'false'
-    #   buildDependsOn:
-    #     - rocBLAS_build
-    #   unifiedBuild:
-    #     downstreamAggregateNames: rocBLAS+rocPRIM
-    #     buildDependsOn:
-    #       - rocBLAS_build
-    #       - rocPRIM_build
+#    - rocSOLVER:
+#      name: rocSOLVER
+#      sparseCheckoutDir: projects/rocsolver
+#      skipUnifiedBuild: 'false'
+#      buildDependsOn:
+#        - rocBLAS_build
+#      unifiedBuild:
+#        downstreamAggregateNames: rocBLAS+rocPRIM
+#        buildDependsOn:
+#          - rocBLAS_build
+#          - rocPRIM_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:

.azuredevops/components/rocFFT.yml

@@ -78,19 +78,19 @@ parameters:
         target: gfx942
       - gfx90a:
         target: gfx90a
-# - name: downstreamComponentMatrix
-#   type: object
-#   default:
-#     - hipFFT:
-#       name: hipFFT
-#       sparseCheckoutDir: projects/hipfft
-#       skipUnifiedBuild: 'false'
-#       buildDependsOn:
-#         - rocFFT_build
+- name: downstreamComponentMatrix
+  type: object
+  default:
+    - hipFFT:
+      name: hipFFT
+      sparseCheckoutDir: projects/hipfft
+      skipUnifiedBuild: 'false'
+      buildDependsOn:
+        - rocFFT_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: ${{ parameters.componentName }}_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
     ${{ if parameters.buildDependsOn }}:
       dependsOn:
         - ${{ each build in parameters.buildDependsOn }}:
@@ -151,12 +151,12 @@ jobs:
           - HIP_ROCCLR_HOME:::/home/user/workspace/rocm
 
 - ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: ${{ parameters.componentName }}_test_${{ job.target }}
-    dependsOn: ${{ parameters.componentName }}_build_${{ job.target }}
+  - job: ${{ parameters.componentName }}_test_ubuntu2204_${{ job.target }}
+    dependsOn: ${{ parameters.componentName }}_build_ubuntu2204_${{ job.target }}
     condition:
       and(succeeded(),
         eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
-        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), variables['Build.DefinitionName'])),
+        not(containsValue(split(variables['DISABLED_${{ upper(job.target) }}_TESTS'], ','), '${{ parameters.componentName }}')),
         eq(${{ parameters.aggregatePipeline }}, False)
       )
     variables:
@@ -196,14 +196,14 @@ jobs:
         environment: test
         gpuTarget: ${{ job.target }}
 
-# - ${{ if parameters.triggerDownstreamJobs }}:
-#   - ${{ each component in parameters.downstreamComponentMatrix }}:
-#     - ${{ if not(and(parameters.unifiedBuild, eq(component.skipUnifiedBuild, 'true'))) }}:
-#       - template: /.azuredevops/components/${{ component.name }}.yml@pipelines_repo
-#         parameters:
-#           checkoutRepo: ${{ parameters.checkoutRepo }}
-#           sparseCheckoutDir: ${{ component.sparseCheckoutDir }}
-#           buildDependsOn: ${{ component.buildDependsOn }}
-#           downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ parameters.componentName }}
-#           triggerDownstreamJobs: true
-#           unifiedBuild: ${{ parameters.unifiedBuild }}
+- ${{ if parameters.triggerDownstreamJobs }}:
+  - ${{ each component in parameters.downstreamComponentMatrix }}:
+    - ${{ if not(and(parameters.unifiedBuild, eq(component.skipUnifiedBuild, 'true'))) }}:
+      - template: /.azuredevops/components/${{ component.name }}.yml@pipelines_repo
+        parameters:
+          checkoutRepo: ${{ parameters.checkoutRepo }}
+          sparseCheckoutDir: ${{ component.sparseCheckoutDir }}
+          buildDependsOn: ${{ component.buildDependsOn }}
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ parameters.componentName }}
+          triggerDownstreamJobs: true
+          unifiedBuild: ${{ parameters.unifiedBuild }}

.azuredevops/components/rocPRIM.yml

@@ -91,12 +91,12 @@ parameters:
         - rocPRIM_build
     # rocSOLVER depends on both rocBLAS and rocPRIM
     # for a unified build, rocBLAS will be the one to call rocSOLVER
-    # - rocSOLVER:
-    #   name: rocSOLVER
-    #   sparseCheckoutDir: projects/rocsolver
-    #   skipUnifiedBuild: 'true'
-    #   buildDependsOn:
-    #     - rocPRIM_build
+#    - rocSOLVER:
+#      name: rocSOLVER
+#      sparseCheckoutDir: projects/rocsolver
+#      skipUnifiedBuild: 'true'
+#      buildDependsOn:
+#        - rocPRIM_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:

.azuredevops/components/rocRAND.yml

@@ -79,6 +79,12 @@ parameters:
       skipUnifiedBuild: 'false'
       buildDependsOn:
         - rocRAND_build
+    - MIOpen:
+      name: MIOpen
+      sparseCheckoutDir: projects/miopen
+      skipUnifiedBuild: 'true'
+      buildDependsOn:
+        - rocRAND_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:

.azuredevops/components/rocSOLVER.yml

@@ -83,6 +83,28 @@ parameters:
     testJobs:
       - { os: ubuntu2204, packageManager: apt, target: gfx942 }
       - { os: ubuntu2204, packageManager: apt, target: gfx90a }
+- name: downstreamComponentMatrix
+  type: object
+  default:
+    - hipBLAS:
+      name: hipBLAS
+      sparseCheckoutDir: projects/hipblas
+      skipUnifiedBuild: 'false'
+      buildDependsOn:
+        - rocSOLVER_build
+    # hipSOLVER depends on both rocSOLVER and rocSPARSE
+    # for a unified build, rocSOLVER will be the one to call hipSOLVER
+#    - hipSOLVER:
+#      name: hipSOLVER
+#      sparseCheckoutDir: projects/hipsolver
+#      skipUnifiedBuild: 'false'
+#      buildDependsOn:
+#        - rocSOLVER_build
+#      unifiedBuild:
+#        downstreamAggregateNames: rocSOLVER+rocSPARSE
+#        buildDependsOn:
+#          - rocSOLVER_build
+#          - rocSPARSE_build
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
@@ -228,3 +250,19 @@ jobs:
           aptPackages: ${{ parameters.aptPackages }}
           environment: test
           gpuTarget: ${{ job.target }}
+
+- ${{ if parameters.triggerDownstreamJobs }}:
+  - ${{ each component in parameters.downstreamComponentMatrix }}:
+    - ${{ if not(and(parameters.unifiedBuild, eq(component.skipUnifiedBuild, 'true'))) }}:
+      - template: /.azuredevops/components/${{ component.name }}.yml@pipelines_repo
+        parameters:
+          checkoutRepo: ${{ parameters.checkoutRepo }}
+          sparseCheckoutDir: ${{ component.sparseCheckoutDir }}
+          triggerDownstreamJobs: true
+          unifiedBuild: ${{ parameters.unifiedBuild }}
+          ${{ if parameters.unifiedBuild }}:
+            buildDependsOn: ${{ component.unifiedBuild.buildDependsOn }}
+            downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ component.unifiedBuild.downstreamAggregateNames }}
+          ${{ else }}:
+            buildDependsOn: ${{ component.buildDependsOn }}
+            downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}+${{ parameters.componentName }}

.azuredevops/components/rocm-libraries.yml

@@ -0,0 +1,163 @@
+parameters:
+- name: componentName
+  type: string
+  default: rocm_libraries
+- name: checkoutRepo
+  type: string
+  default: 'self'
+- name: checkoutRef
+  type: string
+  default: ''
+# monorepo related parameters
+- name: sparseCheckoutDir
+  type: string
+  default: ''
+- name: triggerDownstreamJobs
+  type: boolean
+  default: false
+- name: downstreamAggregateNames
+  type: string
+  default: ''
+- name: buildDependsOn
+  type: object
+  default: null
+- name: unifiedBuild
+  type: boolean
+  default: false
+# set to true if doing full build of ROCm stack
+# and dependencies are pulled from same pipeline
+- name: aggregatePipeline
+  type: boolean
+  default: false
+- name: aptPackages
+  type: object
+  default:
+    - ccache
+    - gfortran
+    - git
+    - libdrm-dev
+    - libmsgpack-dev
+    - libnuma-dev
+    - ninja-build
+    - python3-pip
+    - python3-venv
+- name: pipModules
+  type: object
+  default:
+    - joblib
+    - "packaging>=22.0"
+    - --upgrade
+- name: rocmDependencies
+  type: object
+  default:
+    - aomp
+    - clr
+    - llvm-project
+    - rocminfo
+    - rocm-cmake
+    - rocm_smi_lib
+    - rocprofiler-register
+    - ROCR-Runtime
+    - roctracer
+- name: rocmTestDependencies
+  type: object
+  default:
+    - aomp
+    - clr
+    - llvm-project
+    - rocminfo
+    - rocm_smi_lib
+    - rocprofiler-register
+    - ROCR-Runtime
+    - roctracer
+
+- name: jobMatrix
+  type: object
+  default:
+    buildJobs:
+      - { pool: rocm-ci_ultra_build_pool, os: ubuntu2204, packageManager: apt, target: gfx942 }
+
+jobs:
+- ${{ each job in parameters.jobMatrix.buildJobs }}:
+  - job: ${{ parameters.componentName }}_build_${{ job.os }}_${{ job.target }}
+    timeoutInMinutes: 300
+    ${{ if parameters.buildDependsOn }}:
+      dependsOn:
+        - ${{ each build in parameters.buildDependsOn }}:
+          - ${{ build }}_${{ job.os }}
+    variables:
+    - group: common
+    - template: /.azuredevops/variables-global.yml
+    - name: DAY_STRING
+      value: $[format('{0:ddMMyyyy}', pipeline.startTime)]
+    pool: ${{ job.pool }}
+    ${{ if eq(job.os, 'almalinux8') }}:
+      container:
+        image: rocmexternalcicd.azurecr.io/manylinux228:latest
+        endpoint: ContainerService3
+    workspace:
+      clean: all
+    steps:
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
+      parameters:
+        aptPackages: ${{ parameters.aptPackages }}
+        pipModules: ${{ parameters.pipModules }}
+        packageManager: ${{ job.packageManager }}
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-cmake-latest.yml
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
+      parameters:
+        checkoutRepo: ${{ parameters.checkoutRepo }}
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-vendor.yml
+      parameters:
+        dependencyList:
+          - gtest
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
+      parameters:
+        checkoutRef: ${{ parameters.checkoutRef }}
+        dependencyList: ${{ parameters.rocmDependencies }}
+        os: ${{ job.os }}
+        gpuTarget: ${{ job.target }}
+        aggregatePipeline: ${{ parameters.aggregatePipeline }}
+        ${{ if parameters.triggerDownstreamJobs }}:
+          downstreamAggregateNames: ${{ parameters.downstreamAggregateNames }}
+    - script: |
+        mkdir -p $(CCACHE_DIR)
+        echo "##vso[task.prependpath]/usr/lib/ccache"
+      displayName: Update path for ccache
+    - task: Cache@2
+      displayName: Ccache caching
+      inputs:
+        key: rocm-libraries | ${{ job.os }} | ${{ job.target }} | $(DAY_STRING) | $(Agent.BuildDirectory)/rocm/llvm/bin/amdclang++
+        path: $(CCACHE_DIR)
+        restoreKeys: |
+          rocm-libraries | ${{ job.os }} | ${{ job.target }} | $(DAY_STRING)
+          rocm-libraries | ${{ job.os }} | ${{ job.target }}
+          rocm-libraries | ${{ job.os }}
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
+      parameters:
+        os: ${{ job.os }}
+        extraBuildFlags: >-
+          -DROCM_LIBRARIES_SUPERBUILD=ON
+          -GNinja
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
+      parameters:
+        componentName: ${{ parameters.componentName }}
+        os: ${{ job.os }}
+        gpuTarget: ${{ job.target }}
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
+      parameters:
+        componentName: ${{ parameters.componentName }}
+        os: ${{ job.os }}
+        gpuTarget: ${{ job.target }}
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
+    - ${{ if eq(job.os, 'ubuntu2204') }}:
+      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
+        parameters:
+          aptPackages: ${{ parameters.aptPackages }}
+          pipModules: ${{ parameters.pipModules }}
+          gpuTarget: ${{ job.target }}
+          extraPaths: /home/user/workspace/rocm/llvm/bin:/home/user/workspace/rocm/bin
+          installLatestCMake: true
+          extraCopyDirectories:
+            - deps

.azuredevops/components/rocprofiler-compute.yml

@@ -65,43 +65,19 @@ parameters:
   type: object
   default:
     buildJobs:
-      - gfx942-staging:
-        name: gfx942_staging
+      - gfx942:
         target: gfx942
-        dependencySource: staging
-      - gfx942-mainline:
-        name: gfx942_mainline
-        target: gfx942
-        dependencySource: mainline
-      - gfx90a-staging:
-        name: gfx90a_staging
+      - gfx90a:
         target: gfx90a
-        dependencySource: staging
-      - gfx90a-mainline:
-        name: gfx90a_mainline
-        target: gfx90a
-        dependencySource: mainline
     testJobs:
-      - gfx942-staging:
-        name: gfx942_staging
+      - gfx942:
         target: gfx942
-        dependencySource: staging
-      - gfx942-mainline:
-        name: gfx942_mainline
-        target: gfx942
-        dependencySource: mainline
-      - gfx90a-staging:
-        name: gfx90a_staging
+      - gfx90a:
         target: gfx90a
-        dependencySource: staging
-      - gfx90a-mainline:
-        name: gfx90a_mainline
-        target: gfx90a
-        dependencySource: mainline
 
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: rocprofiler_compute_build_${{ job.name }}
+  - job: rocprofiler_compute_build_${{ job.target }}
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -124,11 +100,9 @@ jobs:
           -GNinja
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
       parameters:
-        artifactName: ${{ job.dependencySource }}
         gpuTarget: ${{ job.target }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
       parameters:
-        artifactName: ${{ job.dependencySource }}
         gpuTarget: ${{ job.target }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
     # - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
@@ -138,9 +112,9 @@ jobs:
     #     gpuTarget: ${{ job.target }}
 
 - ${{ each job in parameters.jobMatrix.testJobs }}:
-  - job: rocprofiler_compute_test_${{ job.name }}
+  - job: rocprofiler_compute_test_${{ job.target }}
     timeoutInMinutes: 120
-    dependsOn: rocprofiler_compute_build_${{ job.name }}
+    dependsOn: rocprofiler_compute_build_${{ job.target }}
     condition:
       and(succeeded(),
         eq(variables['ENABLE_${{ upper(job.target) }}_TESTS'], 'true'),
@@ -166,14 +140,12 @@ jobs:
         checkoutRepo: ${{ parameters.checkoutRepo }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
       parameters:
-        postTargetFilter: ${{ job.dependencySource }}
         gpuTarget: ${{ job.target }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
       parameters:
         checkoutRef: ${{ parameters.checkoutRef }}
         dependencyList: ${{ parameters.rocmTestDependencies }}
-        dependencySource: ${{ job.dependencySource }}
         gpuTarget: ${{ job.target }}
     - task: Bash@3
       displayName: Add en_US.UTF-8 locale

.azuredevops/components/rocprofiler-register.yml

@@ -1,10 +1,29 @@
 parameters:
+- name: componentName
+  type: string
+  default: rocprofiler-register
 - name: checkoutRepo
   type: string
   default: 'self'
 - name: checkoutRef
   type: string
   default: ''
+# monorepo related parameters
+- name: sparseCheckoutDir
+  type: string
+  default: ''
+- name: triggerDownstreamJobs
+  type: boolean
+  default: false
+- name: downstreamAggregateNames
+  type: string
+  default: ''
+- name: buildDependsOn
+  type: object
+  default: null
+- name: unifiedBuild
+  type: boolean
+  default: false
 # set to true if doing full build of ROCm stack
 # and dependencies are pulled from same pipeline
 - name: aggregatePipeline
@@ -27,6 +46,10 @@ parameters:
 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
   - job: rocprofiler_register_${{ job.os }}
+    ${{ if parameters.buildDependsOn }}:
+      dependsOn:
+        - ${{ each build in parameters.buildDependsOn }}:
+          - ${{ build }}_${{ job.os }}
     pool:
       ${{ if eq(job.os, 'ubuntu2404') }}:
         vmImage: 'ubuntu-24.04'
@@ -50,9 +73,10 @@ jobs:
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
       parameters:
         checkoutRepo: ${{ parameters.checkoutRepo }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
       parameters:
-        componentName: rocprofiler-register
+        componentName: ${{ parameters.componentName }}
         os: ${{ job.os }}
         useAmdclang: false
         extraBuildFlags: >-
@@ -62,12 +86,16 @@ jobs:
           -GNinja
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
       parameters:
-        componentName: rocprofiler-register
+        componentName: ${{ parameters.componentName }}
+        testDir: $(Agent.BuildDirectory)/s/build
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
       parameters:
+        componentName: ${{ parameters.componentName }}
+        sparseCheckoutDir: ${{ parameters.sparseCheckoutDir }}
         os: ${{ job.os }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
       parameters:
+        componentName: ${{ parameters.componentName }}
         os: ${{ job.os }}
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
     # - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml

.azuredevops/components/rocprofiler-systems.yml

@@ -37,6 +37,7 @@ parameters:
     - libpfm4-dev
     - libtool
     - libopenmpi-dev
+    - libsqlite3-dev
     - m4
     - ninja-build
     - openmpi-bin

.azuredevops/dependencies/boost.yml

@@ -40,7 +40,6 @@ jobs:
   - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
     parameters:
       dependencyList: ${{ parameters.rocmDependencies }}
-      dependencySource: staging
   - task: Bash@3
     displayName: Add ROCm binaries to PATH
     inputs:

.azuredevops/nightly/pytorch.yml

@@ -219,7 +219,6 @@ jobs:
   - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
     parameters:
       dependencyList: ${{ parameters.rocmDependencies }}
-      dependencySource: staging
       gpuTarget: $(JOB_GPU_TARGET)
       setupHIPLibrarySymlinks: true
   - task: Bash@3
@@ -406,7 +405,6 @@ jobs:
     parameters:
       dependencyList: ${{ parameters.rocmTestDependencies }}
       gpuTarget: $(JOB_GPU_TARGET)
-      dependencySource: staging
 # get sources to run test scripts
   - task: Bash@3
     displayName: git clone upstream pytorch

.azuredevops/nightly/rocm-nightly.yml

@@ -3,21 +3,21 @@ parameters:
 - name: jobList
   type: object
   default:
-    - { os: ubuntu2204, target: gfx942, source: staging }
-    - { os: ubuntu2204, target: gfx90a, source: staging }
-    - { os: ubuntu2204, target: gfx1201, source: staging }
-    - { os: ubuntu2204, target: gfx1100, source: staging }
-    - { os: ubuntu2204, target: gfx1030, source: staging }
-    - { os: ubuntu2404, target: gfx942, source: staging }
-    - { os: ubuntu2404, target: gfx90a, source: staging }
-    - { os: ubuntu2404, target: gfx1201, source: staging }
-    - { os: ubuntu2404, target: gfx1100, source: staging }
-    - { os: ubuntu2404, target: gfx1030, source: staging }
-    - { os: almalinux8, target: gfx942, source: staging }
-    - { os: almalinux8, target: gfx90a, source: staging }
-    - { os: almalinux8, target: gfx1201, source: staging }
-    - { os: almalinux8, target: gfx1100, source: staging }
-    - { os: almalinux8, target: gfx1030, source: staging }
+    - { os: ubuntu2204, packageManager: apt, target: gfx942 }
+    - { os: ubuntu2204, packageManager: apt, target: gfx90a }
+    - { os: ubuntu2204, packageManager: apt, target: gfx1201 }
+    - { os: ubuntu2204, packageManager: apt, target: gfx1100 }
+    - { os: ubuntu2204, packageManager: apt, target: gfx1030 }
+    - { os: ubuntu2404, packageManager: apt, target: gfx942 }
+    - { os: ubuntu2404, packageManager: apt, target: gfx90a }
+    - { os: ubuntu2404, packageManager: apt, target: gfx1201 }
+    - { os: ubuntu2404, packageManager: apt, target: gfx1100 }
+    - { os: ubuntu2404, packageManager: apt, target: gfx1030 }
+    - { os: almalinux8, packageManager: dnf, target: gfx942 }
+    - { os: almalinux8, packageManager: dnf, target: gfx90a }
+    - { os: almalinux8, packageManager: dnf, target: gfx1201 }
+    - { os: almalinux8, packageManager: dnf, target: gfx1100 }
+    - { os: almalinux8, packageManager: dnf, target: gfx1030 }
 - name: rocmDependencies
   type: object
   default:
@@ -92,7 +92,8 @@ schedules:
 
 jobs:
 - ${{ each job in parameters.jobList }}:
-  - job: rocm_nightly_${{ job.os }}_${{ job.target }}_${{ job.source }}
+  - job: nightly_${{ job.os }}_${{ job.target }}
+    timeoutInMinutes: 90
     variables:
     - group: common
     - template: /.azuredevops/variables-global.yml
@@ -115,7 +116,6 @@ jobs:
       displayName: System disk space before ROCm
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-rocm.yml
       parameters:
-        dependencySource: ${{ job.source }}
         dependencyList: ${{ parameters.rocmDependencies }}
         os: ${{ job.os }}
         gpuTarget: ${{ job.target }}
@@ -131,7 +131,7 @@ jobs:
         includeRootFolder: false
         archiveType: tar
         tarCompression: gz
-        archiveFile: $(Build.ArtifactStagingDirectory)/$(Build.DefinitionName)_$(Build.BuildNumber)_ubuntu2204_${{ job.target }}.tar.gz
+        archiveFile: $(Build.ArtifactStagingDirectory)/$(Build.DefinitionName)_$(Build.BuildNumber)_${{ job.os }}_${{ job.target }}.tar.gz
     - script: du -sh $(Build.ArtifactStagingDirectory)
       displayName: Compressed ROCm size
     - task: PublishPipelineArtifact@1
@@ -144,5 +144,95 @@ jobs:
       inputs:
         workingDirectory: $(Pipeline.Workspace)
         targetType: inline
-        script: echo "$(Build.DefinitionName)_$(Build.BuildNumber)_ubuntu2204_${{ job.target }}.tar.gz" >> pipelineArtifacts.txt
+        script: echo "$(Build.DefinitionName)_$(Build.BuildNumber)_${{ job.os }}_${{ job.target }}.tar.gz" >> pipelineArtifacts.txt
     - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
+    - ${{ if eq(job.packageManager, 'apt') }}:
+      - task: Bash@3
+        displayName: Create Dockerfile
+        inputs:
+          workingDirectory: $(Agent.BuildDirectory)
+          targetType: inline
+          script: |
+            cat <<'EOF' > Dockerfile
+              ${{ iif(eq(job.os, 'ubuntu2204'), 'FROM ubuntu:22.04', '') }}
+              ${{ iif(eq(job.os, 'ubuntu2404'), 'FROM ubuntu:24.04', '') }}
+
+              WORKDIR /root
+              RUN mkdir rocm
+
+              RUN apt update \
+                && apt upgrade -y \
+                && apt install -y cmake curl git gcc g++ gpg lsb-release lsof ninja-build pkg-config python3 python3-pip wget zip libdrm-dev libelf-dev libgtest-dev libhsakmt-dev libhwloc-dev libnuma-dev libstdc++-12-dev libtbb-dev jq \
+                && apt clean all
+
+              RUN PACKAGE_NAME=$(curl -s https://repo.radeon.com/rocm/apt/latest/pool/main/h/hsa-amd-aqlprofile/ | grep -oP "href=\"\K[^\"]*$(lsb_release -rs)[^\"]*\.deb") \
+                && wget -nv --retry-connrefused https://repo.radeon.com/rocm/apt/latest/pool/main/h/hsa-amd-aqlprofile/$PACKAGE_NAME \
+                && mkdir hsa-amd-aqlprofile \
+                && dpkg-deb -R $PACKAGE_NAME hsa-amd-aqlprofile \
+                && cp -R hsa-amd-aqlprofile/opt/rocm-*/* rocm
+
+              RUN ARTIFACT_URL="https://dev.azure.com/ROCm-CI/ROCm-CI/_apis/build/builds/$(Build.BuildId)/artifacts?artifactName=nightly${{ job.os }}${{ job.target }}&api-version=7.1" \
+                && DOWNLOAD_URL=$(curl -s $ARTIFACT_URL | jq ".resource.downloadUrl" | tr -d '"') \
+                && wget -nv --retry-connrefused $DOWNLOAD_URL -O nightly.zip \
+                && unzip nightly.zip \
+                && tar -xf nightly${{ job.os }}${{ job.target }}/rocm-nightly*${{ job.os }}*${{ job.target }}*.tar.gz -C rocm
+
+              RUN echo /root/rocm/lib | tee /etc/ld.so.conf.d/rocm-ci.conf
+              RUN echo /root/rocm/llvm/lib | tee -a /etc/ld.so.conf.d/rocm-ci.conf
+              RUN echo /root/rocm/lib64 | tee -a /etc/ld.so.conf.d/rocm-ci.conf
+              RUN echo /root/rocm/llvm/lib64 | tee -a /etc/ld.so.conf.d/rocm-ci.conf
+              RUN ldconfig -v
+              ENV PATH="$PATH:/root/rocm/bin"
+              ENTRYPOINT ["/bin/bash"]
+            EOF
+            cat Dockerfile
+    - ${{ elseif eq(job.packageManager, 'dnf') }}:
+      - task: Bash@3
+        displayName: Create Dockerfile
+        inputs:
+          workingDirectory: $(Agent.BuildDirectory)
+          targetType: inline
+          script: |
+            cat <<'EOF' > Dockerfile
+              ${{ iif(eq(job.os, 'almalinux8'), 'FROM almalinux:8', '') }}
+
+              WORKDIR /root
+              RUN mkdir rocm
+
+              RUN dnf install -y cmake curl git gcc gcc-c++ gnupg2 redhat-lsb-core lsof pkgconf python3 python3-pip wget zip libdrm-devel elfutils-libelf-devel numactl-devel libstdc++-devel tbb-devel jq \
+                && dnf clean all
+
+              RUN PACKAGE_NAME=$(curl -s https://repo.radeon.com/rocm/rhel8/$(REPO_RADEON_VERSION)/main/ | grep -oP "hsa-amd-aqlprofile-[^\"]+\.rpm" | head -n1) \
+                && wget -nv --retry-connrefused https://repo.radeon.com/rocm/rhel8/$(REPO_RADEON_VERSION)/main/$PACKAGE_NAME \
+                && mkdir hsa-amd-aqlprofile \
+                && dnf -y install rpm-build cpio \
+                && rpm2cpio $PACKAGE_NAME | (cd hsa-amd-aqlprofile && cpio -idmv) \
+                && cp -R hsa-amd-aqlprofile/opt/rocm-*/* rocm
+
+              RUN ARTIFACT_URL="https://dev.azure.com/ROCm-CI/ROCm-CI/_apis/build/builds/$(Build.BuildId)/artifacts?artifactName=nightly${{ job.os }}${{ job.target }}&api-version=7.1" \
+                && DOWNLOAD_URL=$(curl -s $ARTIFACT_URL | jq ".resource.downloadUrl" | tr -d '"') \
+                && wget -nv --retry-connrefused $DOWNLOAD_URL -O nightly.zip \
+                && UNZIP_DISABLE_ZIPBOMB_DETECTION=TRUE unzip nightly.zip \
+                && tar -xf nightly${{ job.os }}${{ job.target }}/rocm-nightly*${{ job.os }}*${{ job.target }}*.tar.gz -C rocm
+
+              RUN echo /root/rocm/lib | tee /etc/ld.so.conf.d/rocm-ci.conf
+              RUN echo /root/rocm/llvm/lib | tee -a /etc/ld.so.conf.d/rocm-ci.conf
+              RUN echo /root/rocm/lib64 | tee -a /etc/ld.so.conf.d/rocm-ci.conf
+              RUN echo /root/rocm/llvm/lib64 | tee -a /etc/ld.so.conf.d/rocm-ci.conf
+              RUN ldconfig -v
+              ENV PATH="$PATH:/root/rocm/bin"
+              ENTRYPOINT ["/bin/bash"]
+            EOF
+            cat Dockerfile
+    - task: Docker@2
+      displayName: Build and upload Docker image
+      inputs:
+        containerRegistry: ContainerService3
+        repository: 'nightly-${{ job.os }}-${{ job.target }}'
+        Dockerfile: '$(Agent.BuildDirectory)/Dockerfile'
+        buildContext: '$(Agent.BuildDirectory)'
+    - task: Bash@3
+      displayName: '!! Docker Run Command !!'
+      inputs:
+        targetType: inline
+        script: echo "docker run -it --network=host --device=/dev/kfd --device=/dev/dri --security-opt seccomp=unconfined rocmexternalcicd.azurecr.io/nightly-${{ job.os }}-${{ job.target }}:$(Build.BuildId)" | tr '[:upper:]' '[:lower:]'

.azuredevops/templates/steps/dependencies-rocm.yml

@@ -3,13 +3,6 @@ parameters:
 - name: checkoutRef
   type: string
   default: ''
-- name: dependencySource # optional, overrides checkoutRef
-  type: string
-  default: null
-  values:
-    - null # empty strings aren't allowed as values, use null instead
-    - staging
-    - mainline
 - name: dependencyList
   type: object
   default: []
@@ -38,309 +31,240 @@ parameters:
   type: object
   default:
     AMDMIGraphX:
-      pipelineId: $(AMDMIGRAPHX_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: master
+      pipelineId: 113
+      developBranch: develop
       hasGpuTarget: true
     amdsmi:
-      pipelineId: $(AMDSMI_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 99
+      developBranch: amd-staging
       hasGpuTarget: false
     aomp-extras:
-      pipelineId: $(AOMP_EXTRAS_PIPELINE_ID)
-      stagingBranch: aomp-dev
-      mainlineBranch: aomp-dev
+      pipelineId: 111
+      developBranch: aomp-dev
       hasGpuTarget: false
     aomp:
-      pipelineId: $(AOMP_PIPELINE_ID)
-      stagingBranch: aomp-dev
-      mainlineBranch: amd-mainline
+      pipelineId: 115
+      developBranch: aomp-dev
       hasGpuTarget: false
     clr:
-      pipelineId: $(CLR_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 145
+      developBranch: amd-staging
       hasGpuTarget: false
     composable_kernel:
-      pipelineId: $(COMPOSABLE_KERNEL_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 86
+      developBranch: develop
       hasGpuTarget: true
     half:
-      pipelineId: $(HALF_PIPELINE_ID)
-      stagingBranch: rocm
-      mainlineBranch: rocm
+      pipelineId: 101
+      developBranch: rocm
       hasGpuTarget: false
     HIP:
-      pipelineId: $(HIP_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 93
+      developBranch: amd-staging
       hasGpuTarget: false
     hip-tests:
-      pipelineId: $(HIP_TESTS_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 233
+      developBranch: amd-staging
       hasGpuTarget: false
     hipBLAS:
-      pipelineId: $(HIPBLAS_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 317
+      developBranch: develop
       hasGpuTarget: true
     hipBLASLt:
-      pipelineId: $(HIPBLASLT_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 301
+      developBranch: develop
       hasGpuTarget: true
     hipBLAS-common:
-      pipelineId: $(HIPBLAS_COMMON_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 300
+      developBranch: develop
       hasGpuTarget: false
     hipCUB:
-      pipelineId: $(HIPCUB_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: develop
+      pipelineId: 277
+      developBranch: develop
       hasGpuTarget: true
     hipFFT:
-      pipelineId: $(HIPFFT_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 283
+      developBranch: develop
       hasGpuTarget: true
     hipfort:
-      pipelineId: $(HIPFORT_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 102
+      developBranch: develop
       hasGpuTarget: false
     HIPIFY:
-      pipelineId: $(HIPIFY_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 92
+      developBranch: amd-staging
       hasGpuTarget: false
     hipRAND:
-      pipelineId: $(HIPRAND_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: develop
+      pipelineId: 275
+      developBranch: develop
       hasGpuTarget: true
     hipSOLVER:
-      pipelineId: $(HIPSOLVER_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 84
+      developBranch: develop
       hasGpuTarget: true
     hipSPARSE:
-      pipelineId: $(HIPSPARSE_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 315
+      developBranch: develop
       hasGpuTarget: true
     hipSPARSELt:
-      pipelineId: $(HIPSPARSELT_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 309
+      developBranch: develop
       hasGpuTarget: true
     hipTensor:
-      pipelineId: $(HIPTENSOR_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 105
+      developBranch: develop
       hasGpuTarget: true
     llvm-project:
-      pipelineId: $(LLVM_PROJECT_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 2
+      developBranch: amd-staging
       hasGpuTarget: false
     MIOpen:
-      pipelineId: $(MIOpen_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: amd-master
+      pipelineId: 320
+      developBranch: develop
       hasGpuTarget: true
     MIVisionX:
-      pipelineId: $(MIVISIONX_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: master
-      hasGpuTarget: true
-    omnitrace: # deprecated
-      pipelineId: $(OMNITRACE_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 80
+      developBranch: develop
       hasGpuTarget: true
     rccl:
-      pipelineId: $(RCCL_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 107
+      developBranch: develop
       hasGpuTarget: true
     rdc:
-      pipelineId: $(RDC_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 100
+      developBranch: amd-staging
       hasGpuTarget: false
     rocAL:
-      pipelineId: $(ROCAL_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 151
+      developBranch: develop
       hasGpuTarget: true
     rocALUTION:
-      pipelineId: $(ROCALUTION_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 89
+      developBranch: develop
       hasGpuTarget: true
     rocBLAS:
-      pipelineId: $(ROCBLAS_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 302
+      developBranch: develop
       hasGpuTarget: true
     ROCdbgapi:
-      pipelineId: $(ROCDBGAPI_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 135
+      developBranch: amd-staging
       hasGpuTarget: false
     rocDecode:
-      pipelineId: $(ROCDECODE_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 79
+      developBranch: develop
       hasGpuTarget: false
     rocFFT:
-      pipelineId: $(ROCFFT_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 282
+      developBranch: develop
       hasGpuTarget: true
     ROCgdb:
-      pipelineId: $(ROCGDB_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline-rocgdb-15
+      pipelineId: 134
+      developBranch: amd-staging
       hasGpuTarget: false
     rocJPEG:
-      pipelineId: $(ROCJPEG_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 262
+      developBranch: develop
       hasGpuTarget: false
     rocm-cmake:
-      pipelineId: $(ROCM_CMAKE_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 6
+      developBranch: develop
       hasGpuTarget: false
     rocm-core:
-      pipelineId: $(ROCM_CORE_PIPELINE_ID)
-      stagingBranch: master
-      mainlineBranch: amd-master
+      pipelineId: 103
+      developBranch: master
       hasGpuTarget: false
     rocm-examples:
-      pipelineId: $(ROCM_EXAMPLES_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 216
+      developBranch: amd-staging
       hasGpuTarget: true
     rocminfo:
-      pipelineId: $(ROCMINFO_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 91
+      developBranch: amd-staging
       hasGpuTarget: false
     rocMLIR:
-      pipelineId: $(ROCMLIR_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 229
+      developBranch: develop
       hasGpuTarget: false
     ROCmValidationSuite:
-      pipelineId: $(ROCMVALIDATIONSUITE_PIPELINE_ID)
-      stagingBranch: master
-      mainlineBranch: master
+      pipelineId: 106
+      developBranch: master
       hasGpuTarget: true
     rocm_bandwidth_test:
-      pipelineId: $(ROCM_BANDWIDTH_TEST_PIPELINE_ID)
-      stagingBranch: master
-      mainlineBranch: master
+      pipelineId: 88
+      developBranch: master
       hasGpuTarget: false
     rocm_smi_lib:
-      pipelineId: $(ROCM_SMI_LIB_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 96
+      developBranch: amd-staging
       hasGpuTarget: false
     rocPRIM:
-      pipelineId: $(ROCPRIM_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: develop
+      pipelineId: 273
+      developBranch: develop
       hasGpuTarget: true
     rocprofiler:
-      pipelineId: $(ROCPROFILER_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-master
+      pipelineId: 143
+      developBranch: amd-staging
       hasGpuTarget: true
     rocprofiler-compute:
-      pipelineId: $(ROCPROFILER_COMPUTE_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: amd-mainline
+      pipelineId: 257
+      developBranch: develop
       hasGpuTarget: true
     rocprofiler-register:
-      pipelineId: $(ROCPROFILER_REGISTER_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 327
+      developBranch: develop
       hasGpuTarget: false
     rocprofiler-sdk:
-      pipelineId: $(ROCPROFILER_SDK_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 246
+      developBranch: amd-staging
       hasGpuTarget: true
     rocprofiler-systems:
-      pipelineId: $(ROCPROFILER_SYSTEMS_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 255
+      developBranch: amd-staging
       hasGpuTarget: true
     rocPyDecode:
-      pipelineId: $(ROCPYDECODE_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 239
+      developBranch: develop
       hasGpuTarget: true
     ROCR-Runtime:
-      pipelineId: $(ROCR_RUNTIME_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 10
+      developBranch: amd-staging
       hasGpuTarget: false
     rocRAND:
-      pipelineId: $(ROCRAND_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: develop
+      pipelineId: 274
+      developBranch: develop
       hasGpuTarget: true
     rocr_debug_agent:
-      pipelineId: $(ROCR_DEBUG_AGENT_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 136
+      developBranch: amd-staging
       hasGpuTarget: false
     rocSOLVER:
-      pipelineId: $(ROCSOLVER_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 81
+      developBranch: develop
       hasGpuTarget: true
     rocSPARSE:
-      pipelineId: $(ROCSPARSE_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 314
+      developBranch: develop
       hasGpuTarget: true
-    ROCT-Thunk-Interface: # deprecated
-      pipelineId: $(ROCT_THUNK_INTERFACE_PIPELINE_ID)
-      stagingBranch: master
-      mainlineBranch: master
-      hasGpuTarget: false
     rocThrust:
-      pipelineId: $(ROCTHRUST_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: develop
+      pipelineId: 276
+      developBranch: develop
       hasGpuTarget: true
     roctracer:
-      pipelineId: $(ROCTRACER_PIPELINE_ID)
-      stagingBranch: amd-staging
-      mainlineBranch: amd-mainline
+      pipelineId: 141
+      developBranch: amd-staging
       hasGpuTarget: true
     rocWMMA:
-      pipelineId: $(ROCWMMA_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 109
+      developBranch: develop
       hasGpuTarget: true
     rpp:
-      pipelineId: $(RPP_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 78
+      developBranch: develop
       hasGpuTarget: true
     TransferBench:
-      pipelineId: $(TRANSFERBENCH_PIPELINE_ID)
-      stagingBranch: develop
-      mainlineBranch: mainline
+      pipelineId: 265
+      developBranch: develop
       hasGpuTarget: true
 
 steps:
@@ -356,72 +280,30 @@ steps:
       parameters:
         componentName: ${{ split(dependency, ':')[0] }}
         pipelineId: ${{ parameters.componentVarList[split(dependency, ':')[0]].pipelineId }}
+        branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].developBranch }}
         aggregatePipeline: ${{ parameters.aggregatePipeline }}
         extractAndDeleteFiles: false
-        ${{ if parameters.componentVarList[split(dependency, ':')[0]].hasGpuTarget }}:
-          fileFilter: "${{ split(dependency, ':')[1] }}*_${{ parameters.os }}_${{ parameters.gpuTarget }}"
-        # dependencySource = staging
-        ${{ if eq(parameters.dependencySource, 'staging')}}:
-          branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].stagingBranch }}
-        # dependencySource = mainline
-        ${{ elseif eq(parameters.dependencySource, 'mainline')}}:
-          branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].mainlineBranch }}
-        # checkoutRef = staging
-        ${{ elseif eq(parameters.checkoutRef, parameters.componentVarList[variables['Build.DefinitionName']].stagingBranch) }}:
-          branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].stagingBranch }}
-        # checkoutRef = mainline
-        ${{ elseif eq(parameters.checkoutRef, parameters.componentVarList[variables['Build.DefinitionName']].mainlineBranch) }}:
-          branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].mainlineBranch }}
-        # SourceBranchName = staging
-        ${{ elseif eq(variables['Build.SourceBranchName'], parameters.componentVarlist[variables['Build.DefinitionName']].stagingBranch) }}:
-          branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].stagingBranch }}
-        # SourceBranchName = mainline
-        ${{ elseif eq(variables['Build.SourceBranchName'], parameters.componentVarlist[variables['Build.DefinitionName']].mainlineBranch) }}:
-          branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].mainlineBranch }}
-        # default = staging
-        ${{ else }}:
-          branchName: ${{ parameters.componentVarList[split(dependency, ':')[0]].stagingBranch }}
 # no colon (:) found in this item in the list
   - ${{ elseif containsValue(split(parameters.downstreamAggregateNames, '+'), dependency) }}:
     - template: local-artifact-download.yml
       parameters:
-        ${{ if parameters.componentVarList[dependency].hasGpuTarget }}:
-          gpuTarget: ${{ parameters.gpuTarget }}
+        buildType: current
         preTargetFilter: ${{ dependency }}
         os: ${{ parameters.os }}
-        buildType: current
+        ${{ if parameters.componentVarList[dependency].hasGpuTarget }}:
+          gpuTarget: ${{ parameters.gpuTarget }}
   - ${{ else }}:
     - template: artifact-download.yml
       parameters:
         componentName: ${{ dependency }}
         pipelineId: ${{ parameters.componentVarList[dependency].pipelineId }}
+        branchName: ${{ parameters.componentVarList[dependency].developBranch }}
         aggregatePipeline: ${{ parameters.aggregatePipeline }}
         extractAndDeleteFiles: false
         ${{ if parameters.componentVarList[dependency].hasGpuTarget }}:
           fileFilter: ${{ parameters.os }}_${{ parameters.gpuTarget }}
         ${{ else }}:
           fileFilter: ${{ parameters.os }}
-        # dependencySource = staging
-        ${{ if eq(parameters.dependencySource, 'staging')}}:
-          branchName: ${{ parameters.componentVarList[dependency].stagingBranch }}
-        # dependencySource = mainline
-        ${{ elseif eq(parameters.dependencySource, 'mainline')}}:
-          branchName: ${{ parameters.componentVarList[dependency].mainlineBranch }}
-        # checkoutRef = staging
-        ${{ elseif eq(parameters.checkoutRef, parameters.componentVarList[variables['Build.DefinitionName']].stagingBranch) }}:
-          branchName: ${{ parameters.componentVarList[dependency].stagingBranch }}
-        # checkoutRef = mainline
-        ${{ elseif eq(parameters.checkoutRef, parameters.componentVarList[variables['Build.DefinitionName']].mainlineBranch) }}:
-          branchName: ${{ parameters.componentVarList[dependency].mainlineBranch }}
-        # SourceBranchName = staging
-        ${{ elseif eq(variables['Build.SourceBranchName'], parameters.componentVarlist[variables['Build.DefinitionName']].stagingBranch) }}:
-          branchName: ${{ parameters.componentVarList[dependency].stagingBranch }}
-        # SourceBranchName = mainline
-        ${{ elseif eq(variables['Build.SourceBranchName'], parameters.componentVarlist[variables['Build.DefinitionName']].mainlineBranch) }}:
-          branchName: ${{ parameters.componentVarList[dependency].mainlineBranch }}
-        # default = staging
-        ${{ else }}:
-          branchName: ${{ parameters.componentVarList[dependency].stagingBranch }}
 - task: ExtractFiles@1
   displayName: Extract ROCm artifacts
   inputs:

.azuredevops/templates/steps/miopen-get-ck-build.yml

@@ -7,13 +7,12 @@ steps:
 - task: Bash@3
   name: downloadCKBuild
   displayName: Download specific CK build
-  continueOnError: true
   env:
     CXX: $(Agent.BuildDirectory)/rocm/llvm/bin/amdclang++
     CC: $(Agent.BuildDirectory)/rocm/llvm/bin/amdclang
   inputs:
     targetType: inline
-    workingDirectory: $(Build.SourcesDirectory)
+    workingDirectory: $(Agent.BuildDirectory)/s
     script: |
       AZ_API="https://dev.azure.com/ROCm-CI/ROCm-CI/_apis"
       GH_API="https://api.github.com/repos/ROCm"
@@ -67,7 +66,19 @@ steps:
       fi
 
       echo "Downloading CK artifact from $ARTIFACT_URL"
-      wget --tries=5 --waitretry=10 --retry-connrefused -nv $ARTIFACT_URL -O $(System.ArtifactsDirectory)/ck.zip
+
+      RETRIES=0
+      MAX_RETRIES=5
+      until wget -nv $ARTIFACT_URL -O $(System.ArtifactsDirectory)/ck.zip; do
+        RETRIES=$((RETRIES+1))
+        if [[ $RETRIES -ge $MAX_RETRIES ]]; then
+          echo "Failed to download CK artifact after $MAX_RETRIES attempts."
+          exit 1
+        fi
+        echo "Download failed, retrying ($RETRIES/$MAX_RETRIES)..."
+        sleep 5
+      done
+
       unzip $(System.ArtifactsDirectory)/ck.zip -d $(System.ArtifactsDirectory)
       mkdir -p $(Agent.BuildDirectory)/rocm
       tar -zxvf $(System.ArtifactsDirectory)/composable_kernel*/*.tar.gz -C $(Agent.BuildDirectory)/rocm
@@ -82,4 +93,3 @@ steps:
         fi
         echo "Instead used latest CK build $CK_BUILD_ID for commit $BUILD_COMMIT"
       fi
-      exit $EXIT_CODE

.azuredevops/variables-global.yml

@@ -23,145 +23,25 @@ variables:
   value: rocm-ci_high_build_pool
 - name: ULTRA_BUILD_POOL
   value: rocm-ci_ultra_build_pool
-- name: ON_PREM_BUILD_POOL
-  value: rocm-ci_build_pool
-- name: LARGE_DISK_BUILD_POOL
-  value: rocm-ci_larger_base_disk_pool
 - name: GFX942_TEST_POOL
   value: gfx942_test_pool
 - name: GFX90A_TEST_POOL
   value: gfx90a_test_pool
 - name: LATEST_RELEASE_VERSION
-  value: 6.4.1
+  value: 6.4.2
 - name: REPO_RADEON_VERSION
-  value: 6.4.1
+  value: 6.4.2
 - name: NEXT_RELEASE_VERSION
   value: 7.0.0
 - name: LATEST_RELEASE_TAG
-  value: rocm-6.4.1
+  value: rocm-6.4.2
 - name: DOCKER_SKIP_GFX
   value: gfx90a
-- name: AMDMIGRAPHX_PIPELINE_ID
-  value: 113
-- name: AMDSMI_PIPELINE_ID
-  value: 99
-- name: AOMP_EXTRAS_PIPELINE_ID
-  value: 111
-- name: AOMP_PIPELINE_ID
-  value: 115
-- name: CLR_PIPELINE_ID
-  value: 145
 - name: COMPOSABLE_KERNEL_PIPELINE_ID
   value: 86
-- name: FLANG_LEGACY_PIPELINE_ID
-  value: 77
-- name: HALF_PIPELINE_ID
-  value: 101
 - name: HALF560_PIPELINE_ID
   value: 68
 - name: HALF560_BUILD_ID
   value: 621
 - name: HIP_PIPELINE_ID
   value: 93
-- name: HIP_TESTS_PIPELINE_ID
-  value: 233
-- name: HIPBLAS_COMMON_PIPELINE_ID
-  value: 300
-- name: HIPBLAS_PIPELINE_ID
-  value: 87
-- name: HIPBLASLT_PIPELINE_ID
-  value: 301
-- name: HIPCUB_PIPELINE_ID
-  value: 277
-- name: HIPFFT_PIPELINE_ID
-  value: 121
-- name: HIPFORT_PIPELINE_ID
-  value: 102
-- name: HIPIFY_PIPELINE_ID
-  value: 92
-- name: HIPRAND_PIPELINE_ID
-  value: 275
-- name: HIPSOLVER_PIPELINE_ID
-  value: 84
-- name: HIPSPARSE_PIPELINE_ID
-  value: 83
-- name: HIPSPARSELT_PIPELINE_ID
-  value: 309
-- name: HIPTENSOR_PIPELINE_ID
-  value: 105
-- name: LLVM_PROJECT_PIPELINE_ID
-  value: 2
-- name: MIOPEN_PIPELINE_ID
-  value: 108
-- name: MIVISIONX_PIPELINE_ID
-  value: 80
-- name: RCCL_PIPELINE_ID
-  value: 107
-- name: RDC_PIPELINE_ID
-  value: 100
-- name: ROCAL_PIPELINE_ID
-  value: 151
-- name: ROCALUTION_PIPELINE_ID
-  value: 89
-- name: ROCBLAS_PIPELINE_ID
-  value: 302
-- name: ROCDBGAPI_PIPELINE_ID
-  value: 135
-- name: ROCDECODE_PIPELINE_ID
-  value: 79
-- name: ROCFFT_PIPELINE_ID
-  value: 120
-- name: ROCGDB_PIPELINE_ID
-  value: 134
-- name: ROCJPEG_PIPELINE_ID
-  value: 262
-- name: ROCM_BANDWIDTH_TEST_PIPELINE_ID
-  value: 88
-- name: ROCM_CMAKE_PIPELINE_ID
-  value: 6
-- name: ROCM_CORE_PIPELINE_ID
-  value: 103
-- name: ROCM_EXAMPLES_PIPELINE_ID
-  value: 216
-- name: ROCM_SMI_LIB_PIPELINE_ID
-  value: 96
-- name: ROCMINFO_PIPELINE_ID
-  value: 91
-- name: ROCMLIR_PIPELINE_ID
-  value: 229
-- name: ROCMVALIDATIONSUITE_PIPELINE_ID
-  value: 106
-- name: ROCPRIM_PIPELINE_ID
-  value: 273
-- name: ROCPROFILER_COMPUTE_PIPELINE_ID
-  value: 257
-- name: ROCPROFILER_REGISTER_PIPELINE_ID
-  value: 1
-- name: ROCPROFILER_SDK_PIPELINE_ID
-  value: 246
-- name: ROCPROFILER_SYSTEMS_PIPELINE_ID
-  value: 255
-- name: ROCPROFILER_PIPELINE_ID
-  value: 143
-- name: ROCPYDECODE_PIPELINE_ID
-  value: 239
-- name: ROCR_DEBUG_AGENT_PIPELINE_ID
-  value: 136
-- name: ROCR_RUNTIME_PIPELINE_ID
-  value: 10
-- name: ROCRAND_PIPELINE_ID
-  value: 274
-- name: ROCSOLVER_PIPELINE_ID
-  value: 81
-- name: ROCSPARSE_PIPELINE_ID
-  value: 314
-- name: ROCTHRUST_PIPELINE_ID
-  value: 276
-- name: ROCTRACER_PIPELINE_ID
-  value: 141
-- name: ROCWMMA_PIPELINE_ID
-  value: 109
-- name: RPP_PIPELINE_ID
-  value: 78
-- name: TRANSFERBENCH_PIPELINE_ID
-  value: 265

.wordlist.txt

@@ -5,6 +5,7 @@ ACEs
 ACS
 AccVGPR
 AccVGPRs
+AITER
 ALU
 AllReduce
 AMD
@@ -45,6 +46,7 @@ Bootloader
 CAS
 CCD
 CDNA
+CGUI
 CHTML
 CIFAR
 CLI
@@ -114,12 +116,15 @@ Deprecations
 DevCap
 DirectX
 Dockerfile
+Dockerized
 Doxygen
+dropless
 ELMo
 ENDPGM
 EPYC
 ESXi
 EoS
+fas
 FBGEMM
 FFT
 FFTs
@@ -176,6 +181,7 @@ HBM
 HCA
 HGX
 HIPCC
+hipDataType
 HIPExtension
 HIPIFY
 HIPification
@@ -191,6 +197,7 @@ HWE
 HWS
 Haswell
 Higgs
+href
 Hyperparameters
 Huggingface
 ICD
@@ -270,6 +277,7 @@ Makefiles
 Matplotlib
 Matrox
 MaxText
+Megablocks
 Megatrends
 Megatron
 Mellanox
@@ -279,6 +287,7 @@ Miniconda
 MirroredStrategy
 Mixtral
 MosaicML
+MoEs
 Mpops
 Multicore
 Multithreaded
@@ -355,6 +364,7 @@ PowerEdge
 PowerShell
 Pretrained
 Pretraining
+Primus
 Profiler's
 PyPi
 Pytest
@@ -408,6 +418,7 @@ SDMA
 SDPA
 SDRAM
 SENDMSG
+SGLang
 SGPR
 SGPRs
 SHA
@@ -452,6 +463,8 @@ TPS
 TPU
 TPUs
 TSME
+Taichi
+Taichi's
 Tagram
 TensileLite
 TensorBoard
@@ -516,6 +529,7 @@ Xilinx
 Xnack
 Xteam
 YAML
+YAMLs
 YML
 YModel
 ZeRO
@@ -576,6 +590,7 @@ completers
 composable
 concretization
 config
+configs
 conformant
 constructible
 convolutional
@@ -786,7 +801,9 @@ preprocessing
 preprocessor
 prequantized
 prerequisites
+pretrain
 pretraining
+primus
 profiler
 profilers
 protobuf
@@ -863,6 +880,7 @@ seealso
 sendmsg
 seqs
 serializers
+sglang
 shader
 sharding
 sigmoid

CHANGELOG.md

@@ -4,6 +4,21 @@ This page is a historical overview of changes made to ROCm components. This
 consolidated changelog documents key modifications and improvements across
 different versions of the ROCm software stack and its components.
 
+## ROCm 6.4.3
+
+See the [ROCm 6.4.3 release notes](https://rocm.docs.amd.com/en/docs-6.4.3/about/release-notes.html)
+for a complete overview of this release.
+
+### **ROCm SMI** (7.7.0)
+
+#### Added
+
+- Support for getting the GPU Board voltage.
+
+```{note}
+See the full [ROCm SMI changelog](https://github.com/ROCm/rocm_smi_lib/blob/release/rocm-rel-6.4/CHANGELOG.md) for details, examples, and in-depth descriptions.
+```
+
 ## ROCm 6.4.2
 
 See the [ROCm 6.4.2 release notes](https://rocm.docs.amd.com/en/docs-6.4.2/about/release-notes.html)

README.md

@@ -23,9 +23,6 @@ source software compilers, debuggers, and libraries. ROCm is fully integrated in
 > A new open source build platform for ROCm is under development at
 > https://github.com/ROCm/TheRock, featuring a unified CMake build with bundled
 > dependencies, Windows support, and more.
->
-> The instructions below describe the prior process for building from source
-> which will be replaced once TheRock is mature enough.
 
 ## Getting and Building ROCm from Source
 

RELEASE.md

@@ -10,7 +10,7 @@
 <!-- markdownlint-disable reference-links-images            -->
 <!-- markdownlint-disable no-missing-space-atx              -->
 <!-- spellcheck-disable                                     -->
-# ROCm 6.4.2 release notes
+# ROCm 6.4.3 release notes
 
 The release notes provide a summary of notable changes since the previous ROCm release.
 
@@ -24,8 +24,6 @@ The release notes provide a summary of notable changes since the previous ROCm r
 
 - [ROCm known issues](#rocm-known-issues)
 
-- [ROCm resolved issues](#rocm-resolved-issues)
-
 - [ROCm upcoming changes](#rocm-upcoming-changes)
 
 ```{note}
@@ -35,70 +33,40 @@ documentation to verify compatibility and system requirements.
 
 ## Release highlights
 
-The following are notable new features and improvements in ROCm 6.4.2. For changes to individual components, see
-[Detailed component changes](#detailed-component-changes).
+ROCm 6.4.3 is a quality release that resolves the following issues. For changes to individual components, see [Detailed component changes](#detailed-component-changes).
 
-### ROCm Compute Profiler enhancements
+### AMDGPU driver updates
 
-[ROCm Compute Profiler](https://rocm.docs.amd.com/projects/rocprofiler-compute/en/latest/index.html) includes the following changes:
+* Resolved an issue causing performance degradation in communication operations, caused by increased latency in certain RCCL applications. The fix prevents unnecessary queue eviction during the fork process.
+* Fixed an issue in the AMDGPU driver’s scheduler constraints that could cause queue preemption to fail during workload execution.
 
-* The ``--roofline-data-type`` option now supports FP8, FP16, BF16, FP32, FP64, I8, I32, and I64 data types. This is dependent on the GPU architecture. For more information, see [Roofline options](https://rocm.docs.amd.com/projects/rocprofiler-compute/en/docs-6.4.2/how-to/profile/mode.html#roofline-options).
-
-* ROCm Compute Profiler now uses [AMD SMI](https://rocm.docs.amd.com/projects/amdsmi/en/latest/index.html) instead of [ROCm SMI](https://rocm.docs.amd.com/projects/rocm_smi_lib/en/latest/index.html). The AMD System Management Interface Library (AMD SMI) is a successor to ROCm SMI. It is a unified system management interface tool that provides a user-space interface for applications to monitor and control GPU applications and gives users the ability to query information about drivers and GPUs on the system. For more information, see [https://github.com/ROCm/amdsmi](https://github.com/ROCm/amdsmi) and the [AMD SMI documentation](https://rocm.docs.amd.com/projects/amdsmi/en/latest/index.html).
-
-* ROCm Compute Profiler has added 8-bit floating point (FP8) metrics support for AMD Instinct MI300 series accelerators. For more information, see [System Speed-of-Light](https://rocm.docs.amd.com/projects/rocprofiler-compute/en/docs-6.4.2/conceptual/system-speed-of-light.html).
-
-### rocSOLVER enhancements
-
-rocSOLVER has improved the performance of eigensolvers and singular value decomposition (SVD). For more information, see [rocSOLVER documentation](https://rocm.docs.amd.com/projects/rocSOLVER/en/docs-6.4.2/index.html).
-
-### ROCm Offline Installer Creator updates
-
-The ROCm Offline Installer Creator 6.4.2 includes the following features and improvements:
- 
-* Added support for Oracle Linux 8.10 and 9.6, and SLES 15 SP7.
-* Additional package options for the Offline Installer Creator, including `amd-smi`, `rocdecode`, `rocjpeg`, and `rdc`.
-* ROCm meta packages are now used for selecting ROCm components and use cases.
-* Improved separation of kernel/driver and ROCm prerequisite packages to reduce the size of ROCm-only or driver-only offline installers.
- 
-In addition, the option to build an offline installer based on ROCm version 5.7.3 has been removed. To build an offline installer for ROCm 5.7.3, use the Offline Installer Creator from version 6.4.1 or earlier. See [ROCm Offline Installer Creator](https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.2/install/rocm-offline-installer.html) for more information.
-
-### ROCm Runfile Installer updates
-
-The ROCm Runfile Installer 6.4.2 adds support for Oracle Linux 8.10 and 9.6 (using the RHEL 8 or 9 .run files), Debian 12 (using the Ubuntu 22.04 .run file), and SLES 15 SP7. It also fixes permission settings issues during ROCm and AMDGPU driver installation. For more information, see [ROCm Runfile Installer](https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.2/install/rocm-runfile-installer.html).
+### ROCm SMI update
+* Fixed the failure to load GPU data like System Clock (SCLK) by adjusting the logic for retrieving GPU board voltage.
 
 ### ROCm documentation updates
 
 ROCm documentation continues to be updated to provide clearer and more comprehensive guidance for a wider variety of user needs and use cases.
 
-* [Tutorials for AI developers](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/) have been expanded with the following four new tutorials:
-    * Inference tutorial: [AI agent with MCPs using vLLM and PydanticAI](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/inference/build_airbnb_agent_mcp.html)
-    * GPU development and optimization tutorials:
-        * [Kernel development and optimization with Triton](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/gpu_dev_optimize/triton_kernel_dev.html)
-        * [Profiling Llama-4 inference with vLLM](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/gpu_dev_optimize/llama4_profiling_vllm.html)
-        * [FP8 quantization with AMD Quark for vLLM](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/gpu_dev_optimize/fp8_quantization_quark_vllm.html)
-    
+* [Tutorials for AI developers](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/) have been expanded with the following five new tutorials:
+    * Inference tutorials
+        * [ChatQnA vLLM deployment and performance evaluation](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/inference/opea_deployment_and_evaluation.html)
+        * [Text-to-video generation with ComfyUI](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/inference/t2v_comfyui_radeon.html)
+        * [DeepSeek Janus Pro on CPU or GPU](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/inference/deepseek_janus_cpu_gpu.html)
+        * [DeepSeek-R1 with vLLM V1](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/inference/vllm_v1_DSR1.html)
+    * GPU development and optimization tutorial: [MLA decoding kernel of AITER library](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/notebooks/gpu_dev_optimize/aiter_mla_decode_kernel.html)
+ 
     For more information about the changes, see [Changelog for the AI Developer Hub](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/changelog.html).
 
-* ROCm provides a comprehensive ecosystem for deep learning development. For more details, see [Deep learning frameworks for ROCm](https://rocm.docs.amd.com/en/docs-6.4.2/how-to/deep-learning-rocm.html). As of July 2025, AMD ROCm provides support for the following additional deep learning frameworks:
+* ROCm provides a comprehensive ecosystem for deep learning development. For more details, see [Deep learning frameworks for ROCm](https://rocm.docs.amd.com/en/docs-6.4.3/how-to/deep-learning-rocm.html). AMD ROCm adds support for the following deep learning frameworks:
 
-    * Deep Graph Library is an easy-to-use, high-performance, and scalable Python package for deep learning on graphs. DGL is framework agnostic, meaning if a deep graph model is a component in an end-to-end application, the rest of the logic is implemented using PyTorch. It is currently supported on ROCm 6.4.0. For more information, see [DGL compatibility](https://rocm.docs.amd.com/en/docs-6.4.2/compatibility/ml-compatibility/dgl-compatibility.html).
-    * Stanford Megatron-LM is a large-scale language model training framework. It’s designed to train massive transformer-based language models efficiently by model and data parallelism. It is currently supported on ROCm 6.3.0. For more information, see [Stanford Megatron-LM compatibility](https://rocm.docs.amd.com/en/docs-6.4.2/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.html).
-    * Volcano Engine Reinforcement Learning for LLMs (verl) is a reinforcement learning framework designed for large language models (LLMs). verl offers a scalable, open-source fine-tuning solution optimized for AMD Instinct GPUs with full ROCm support. It is currently supported on ROCm 6.2.0. For more information, see [verl compatibility](https://rocm.docs.amd.com/en/docs-6.4.2/compatibility/ml-compatibility/verl-compatibility.html).
+    * Taichi is an open-source, imperative, and parallel programming language designed for high-performance numerical computation. Embedded in Python, it leverages just-in-time (JIT) compilation frameworks such as LLVM to accelerate compute-intensive Python code by compiling it to native GPU or CPU instructions. It is currently supported on ROCm 6.3.2. For more information, see [Taichi compatibility](https://rocm.docs.amd.com/en/docs-6.4.3/compatibility/ml-compatibility/taichi-compatibility.html).
+    * Megablocks is a light-weight library for mixture-of-experts (MoE) training. The core of the system is efficient "dropless-MoE" and standard MoE layers. Megablocks is integrated with Megatron-LM, where data and pipeline parallel training of MoEs is supported. It is currently supported on ROCm 6.3.0. For more information, see [Megablocks compatibility](https://rocm.docs.amd.com/en/docs-6.4.3/compatibility/ml-compatibility/megablocks-compatibility.html).
 
-* Documentation for the new [ROCprof Compute Viewer](https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/docs-6.4.2/) was added in May 2025. This tool is used to visualize and analyze GPU thread trace data collected using [rocprofv3](https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/latest/index.html). Note that [ROCprof Compute Viewer](https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/docs-6.4.2/) is in an early access state. Running production workloads is not recommended.
-
-* The AMDGPU installer documentation has been removed to encourage the use of the package manager for ROCm installation. While the package manager is the recommended method, you can still install ROCm using the AMDGPU installer by following the [legacy process](https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.1/install/install-methods/amdgpu-installer-index.html). Ensure to update the command with the intended ROCm version before running it. For more information, see [Installation via native package manager](https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.2/install/install-methods/package-manager-index.html).
+* The [Data types and precision support](https://rocm.docs.amd.com/en/latest/reference/precision-support.html) topic now includes new hardware and library support information.
 
 ## Operating system and hardware support changes
 
-ROCm 6.4.2 adds support for SLES 15 SP7. For more information, see [SLES installation](https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.2/install/install-methods/package-manager/package-manager-sles.html).
-
-ROCm 6.4.2 marks the end of support (EoS) for RHEL 9.5. 
-
-ROCm 6.4.2 adds support for RDNA3 architecture-based [Radeon RX 7700 XT](https://www.amd.com/en/products/graphics/desktops/radeon/7000-series/amd-radeon-rx-7700-xt.html) GPU. This GPU is supported on Ubuntu 24.04.2 and RHEL 9.6.
-For details, see the full list of [Supported GPUs
-(Linux)](https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.2/reference/system-requirements.html#supported-gpus).
+Operating system and hardware support remain unchanged in this release.
 
 See the [Compatibility
 matrix](../../docs/compatibility/compatibility-matrix.rst)
@@ -106,8 +74,7 @@ for more information about operating system and hardware compatibility.
 
 ## ROCm components
 
-The following table lists the versions of ROCm components for ROCm 6.4.2, including any version
-changes from 6.4.1 to 6.4.2. Click the component's updated version to go to a list of its changes.
+The following table lists the versions of ROCm components for ROCm 6.4.3.
 Click {fab}`github` to go to the component's source code on GitHub.
 
 <div class="pst-scrollable-table-container">
@@ -129,47 +96,47 @@ Click {fab}`github` to go to the component's source code on GitHub.
             <tr>
                 <th rowspan="9">Libraries</th>
                 <th rowspan="9">Machine learning and computer vision</th>
-                <td><a href="https://rocm.docs.amd.com/projects/composable_kernel/en/docs-6.4.2/index.html">Composable Kernel</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/composable_kernel/en/docs-6.4.3/index.html">Composable Kernel</a></td>
                 <td>1.1.0</td>
                 <td><a href="https://github.com/ROCm/composable_kernel"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/AMDMIGraphX/en/docs-6.4.2/index.html">MIGraphX</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/AMDMIGraphX/en/docs-6.4.3/index.html">MIGraphX</a></td>
                 <td>2.12.0</td>
                 <td><a href="https://github.com/ROCm/AMDMIGraphX"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/MIOpen/en/docs-6.4.2/index.html">MIOpen</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/MIOpen/en/docs-6.4.3/index.html">MIOpen</a></td>
                 <td>3.4.0</td>
                 <td><a href="https://github.com/ROCm/MIOpen"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/MIVisionX/en/docs-6.4.2/index.html">MIVisionX</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/MIVisionX/en/docs-6.4.3/index.html">MIVisionX</a></td>
                 <td>3.2.0</td>
                 <td><a href="https://github.com/ROCm/MIVisionX"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocAL/en/docs-6.4.2/index.html">rocAL</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocAL/en/docs-6.4.3/index.html">rocAL</a></td>
                 <td>2.2.0</td>
                 <td><a href="https://github.com/ROCm/rocAL"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocDecode/en/docs-6.4.2/index.html">rocDecode</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocDecode/en/docs-6.4.3/index.html">rocDecode</a></td>
                 <td>0.10.0</td>
                 <td><a href="https://github.com/ROCm/rocDecode"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocJPEG/en/docs-6.4.2/index.html">rocJPEG</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocJPEG/en/docs-6.4.3/index.html">rocJPEG</a></td>
                 <td>0.8.0</td>
                 <td><a href="https://github.com/ROCm/rocJPEG"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocPyDecode/en/docs-6.4.2/index.html">rocPyDecode</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocPyDecode/en/docs-6.4.3/index.html">rocPyDecode</a></td>
                 <td>0.3.1</td>
                 <td><a href="https://github.com/ROCm/rocPyDecode"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rpp/en/docs-6.4.2/index.html">RPP</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rpp/en/docs-6.4.3/index.html">RPP</a></td>
                 <td>1.9.10</td>
                 <td><a href="https://github.com/ROCm/rpp"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
@@ -178,13 +145,13 @@ Click {fab}`github` to go to the component's source code on GitHub.
             <tr>
                 <th rowspan="2"></th>
                 <th rowspan="2">Communication</th>
-                <td><a href="https://rocm.docs.amd.com/projects/rccl/en/docs-6.4.2/index.html">RCCL</a></td>
-                <td>2.22.3&nbsp;&Rightarrow;&nbsp;<a href="#rccl-2-22-3">2.22.3</td>
+                <td><a href="https://rocm.docs.amd.com/projects/rccl/en/docs-6.4.3/index.html">RCCL</a></td>
+                <td>2.22.3</td>
                 <td><a href="https://github.com/ROCm/rccl"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-            <td><a href="https://rocm.docs.amd.com/projects/rocSHMEM/en/docs-6.4.2/index.html">rocSHMEM</a></td>
-                <td>2.0.0&nbsp;&Rightarrow;&nbsp;<a href="#rocshmem-2-0-1">2.0.1</td>
+            <td><a href="https://rocm.docs.amd.com/projects/rocSHMEM/en/docs-6.4.3/index.html">rocSHMEM</a></td>
+                <td>2.0.1</td>
                 <td><a href="https://github.com/ROCm/rocSHMEM"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
         </tbody>
@@ -192,82 +159,82 @@ Click {fab}`github` to go to the component's source code on GitHub.
             <tr>
                 <th rowspan="16"></th>
                 <th rowspan="16">Math</th>
-                <td><a href="https://rocm.docs.amd.com/projects/hipBLAS/en/docs-6.4.2/index.html">hipBLAS</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipBLAS/en/docs-6.4.3/index.html">hipBLAS</a></td>
                 <td>2.4.0</td>
                 <td><a href="https://github.com/ROCm/hipBLAS"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipBLASLt/en/docs-6.4.2/index.html">hipBLASLt</a></td>
-                <td>0.12.1&nbsp;&Rightarrow;&nbsp;<a href="#hipblaslt-0-12-1">0.12.1</td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipBLASLt/en/docs-6.4.3/index.html">hipBLASLt</a></td>
+                <td>0.12.1</td>
                 <td><a href="https://github.com/ROCm/hipBLASLt"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipFFT/en/docs-6.4.2/index.html">hipFFT</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipFFT/en/docs-6.4.3/index.html">hipFFT</a></td>
                 <td>1.0.18</td>
                 <td><a href="https://github.com/ROCm/hipFFT"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipfort/en/docs-6.4.2/index.html">hipfort</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipfort/en/docs-6.4.3/index.html">hipfort</a></td>
                 <td>0.6.0</td>
                 <td><a href="https://github.com/ROCm/hipfort"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipRAND/en/docs-6.4.2/index.html">hipRAND</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipRAND/en/docs-6.4.3/index.html">hipRAND</a></td>
                 <td>2.12.0</td>
                 <td><a href="https://github.com/ROCm/hipRAND"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipSOLVER/en/docs-6.4.2/index.html">hipSOLVER</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipSOLVER/en/docs-6.4.3/index.html">hipSOLVER</a></td>
                 <td>2.4.0</td>
                 <td><a href="https://github.com/ROCm/hipSOLVER"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipSPARSE/en/docs-6.4.2/index.html">hipSPARSE</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipSPARSE/en/docs-6.4.3/index.html">hipSPARSE</a></td>
                 <td>3.2.0</td>
                 <td><a href="https://github.com/ROCm/hipSPARSE"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipSPARSELt/en/docs-6.4.2/index.html">hipSPARSELt</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipSPARSELt/en/docs-6.4.3/index.html">hipSPARSELt</a></td>
                 <td>0.2.3</td>
                 <td><a href="https://github.com/ROCm/hipSPARSELt"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocALUTION/en/docs-6.4.2/index.html">rocALUTION</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocALUTION/en/docs-6.4.3/index.html">rocALUTION</a></td>
                 <td>3.2.3</td>
                 <td><a href="https://github.com/ROCm/rocALUTION"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocBLAS/en/docs-6.4.2/index.html">rocBLAS</a></td>
-                <td>4.4.0&nbsp;&Rightarrow;&nbsp;<a href="#rocblas-4-4-1">4.4.1</td></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocBLAS/en/docs-6.4.3/index.html">rocBLAS</a></td>
+                <td>4.4.1</td></td>
                 <td><a href="https://github.com/ROCm/rocBLAS"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocFFT/en/docs-6.4.2/index.html">rocFFT</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocFFT/en/docs-6.4.3/index.html">rocFFT</a></td>
                 <td>1.0.32</td>
                 <td><a href="https://github.com/ROCm/rocFFT"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocRAND/en/docs-6.4.2/index.html">rocRAND</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocRAND/en/docs-6.4.3/index.html">rocRAND</a></td>
                 <td>3.3.0</td>
                 <td><a href="https://github.com/ROCm/rocRAND"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocSOLVER/en/docs-6.4.2/index.html">rocSOLVER</a></td>
-                <td>3.28.0&nbsp;&Rightarrow;&nbsp;<a href="#rocsolver-3-28-2">3.28.2</td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocSOLVER/en/docs-6.4.3/index.html">rocSOLVER</a></td>
+                <td>3.28.2</td>
                 <td><a href="https://github.com/ROCm/rocSOLVER"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocSPARSE/en/docs-6.4.2/index.html">rocSPARSE</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocSPARSE/en/docs-6.4.3/index.html">rocSPARSE</a></td>
                 <td>3.4.0</td>
                 <td><a href="https://github.com/ROCm/rocSPARSE"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocWMMA/en/docs-6.4.2/index.html">rocWMMA</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocWMMA/en/docs-6.4.3/index.html">rocWMMA</a></td>
                 <td>1.7.0</td>
                 <td><a href="https://github.com/ROCm/rocWMMA"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/Tensile/en/docs-6.4.2/src/index.html">Tensile</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/Tensile/en/docs-6.4.3/src/index.html">Tensile</a></td>
                 <td>4.43.0</td>
                 <td><a href="https://github.com/ROCm/Tensile"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
@@ -276,22 +243,22 @@ Click {fab}`github` to go to the component's source code on GitHub.
             <tr>
                 <th rowspan="4"></th>
                 <th rowspan="4">Primitives</th>
-                <td><a href="https://rocm.docs.amd.com/projects/hipCUB/en/docs-6.4.2/index.html">hipCUB</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipCUB/en/docs-6.4.3/index.html">hipCUB</a></td>
                 <td>3.4.0</td>
                 <td><a href="https://github.com/ROCm/hipCUB"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/hipTensor/en/docs-6.4.2/index.html">hipTensor</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/hipTensor/en/docs-6.4.3/index.html">hipTensor</a></td>
                 <td>1.5.0</td>
                 <td><a href="https://github.com/ROCm/hipTensor"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocPRIM/en/docs-6.4.2/index.html">rocPRIM</a></td>
-                <td>3.4.0&nbsp;&Rightarrow;&nbsp;<a href="#rocprim-3-4-1">3.4.1</td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocPRIM/en/docs-6.4.3/index.html">rocPRIM</a></td>
+                <td>3.4.1</td>
                 <td><a href="https://github.com/ROCm/rocPRIM"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocThrust/en/docs-6.4.2/index.html">rocThrust</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocThrust/en/docs-6.4.3/index.html">rocThrust</a></td>
                 <td>3.3.0</td>
                 <td><a href="https://github.com/ROCm/rocThrust"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
@@ -300,28 +267,28 @@ Click {fab}`github` to go to the component's source code on GitHub.
             <tr>
                 <th rowspan="7">Tools</th>
                 <th rowspan="7">System management</th>
-                <td><a href="https://rocm.docs.amd.com/projects/amdsmi/en/docs-6.4.2/index.html">AMD SMI</a></td>
-                <td>25.4.2&nbsp;&Rightarrow;&nbsp;<a href="#amd-smi-25-5-1">25.5.1</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/amdsmi/en/docs-6.4.3/index.html">AMD SMI</a></td>
+                <td>25.5.1</a></td>
                 <td><a href="https://github.com/ROCm/amdsmi"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rdc/en/docs-6.4.2/index.html">ROCm Data Center Tool</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rdc/en/docs-6.4.3/index.html">ROCm Data Center Tool</a></td>
                 <td>0.3.0</td>
                 <td><a href="https://github.com/ROCm/rdc"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocminfo/en/docs-6.4.2/index.html">rocminfo</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocminfo/en/docs-6.4.3/index.html">rocminfo</a></td>
                 <td>1.0.0</td>
                 <td><a href="https://github.com/ROCm/rocminfo"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocm_smi_lib/en/docs-6.4.2/index.html">ROCm SMI</a></td>
-                <td>7.5.0</td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocm_smi_lib/en/docs-6.4.3/index.html">ROCm SMI</a></td>
+                <td>7.5.0&nbsp;&Rightarrow;&nbsp;<a href="#rocm-smi-7-7-0">7.7.0</td>
                 <td><a href="https://github.com/ROCm/rocm_smi_lib"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/ROCmValidationSuite/en/docs-6.4.2/index.html">ROCm Validation Suite</a></td>
-                <td>1.1.0&nbsp;&Rightarrow;&nbsp;<a href="#rocm-validation-suite-1-1-0">1.1.0</td>
+                <td><a href="https://rocm.docs.amd.com/projects/ROCmValidationSuite/en/docs-6.4.3/index.html">ROCm Validation Suite</a></td>
+                <td>1.1.0</td>
                 <td><a href="https://github.com/ROCm/ROCmValidationSuite"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
         </tbody>
@@ -329,38 +296,38 @@ Click {fab}`github` to go to the component's source code on GitHub.
             <tr>
                 <th rowspan="6"></th>
                 <th rowspan="6">Performance</th>
-                <td><a href="https://rocm.docs.amd.com/projects/rocm_bandwidth_test/en/docs-6.4.2/index.html">ROCm Bandwidth
+                <td><a href="https://rocm.docs.amd.com/projects/rocm_bandwidth_test/en/docs-6.4.3/index.html">ROCm Bandwidth
                         Test</a></td>
                 <td>1.4.0</td>
                 <td><a href="https://github.com/ROCm/rocm_bandwidth_test/"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler-compute/en/docs-6.4.2/index.html">ROCm Compute Profiler</a></td>
-                <td>3.1.0&nbsp;&Rightarrow;&nbsp;<a href="#rocm-compute-profiler-3-1-1">3.1.1</td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler-compute/en/docs-6.4.3/index.html">ROCm Compute Profiler</a></td>
+                <td>3.1.1</td>
                 <td><a href="https://github.com/ROCm/rocprofiler-compute"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler-systems/en/docs-6.4.2/index.html">ROCm Systems Profiler</a></td>
-                <td>1.0.1&nbsp;&Rightarrow;&nbsp;<a href="#rocm-systems-profiler-1-0-2">1.0.2</td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler-systems/en/docs-6.4.3/index.html">ROCm Systems Profiler</a></td>
+                <td>1.0.2</td>
                 <td><a href="https://github.com/ROCm/rocprofiler-systems"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler/en/docs-6.4.2/index.html">ROCProfiler</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler/en/docs-6.4.3/index.html">ROCProfiler</a></td>
                 <td>2.0.0</td>
                 <td><a href="https://github.com/ROCm/ROCProfiler/"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/docs-6.4.2/index.html">ROCprofiler-SDK</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/docs-6.4.3/index.html">ROCprofiler-SDK</a></td>
                 <td>0.6.0</td>
                 <td><a href="https://github.com/ROCm/rocprofiler-sdk/"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr >
-                <td><a href="https://rocm.docs.amd.com/projects/roctracer/en/docs-6.4.2/index.html">ROCTracer</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/roctracer/en/docs-6.4.3/index.html">ROCTracer</a></td>
                 <td>4.1.0</td>
                 <td><a href="https://github.com/ROCm/ROCTracer/"><i
                             class="fab fa-github fa-lg"></i></a></td>
@@ -370,32 +337,32 @@ Click {fab}`github` to go to the component's source code on GitHub.
             <tr>
                 <th rowspan="5"></th>
                 <th rowspan="5">Development</th>
-                <td><a href="https://rocm.docs.amd.com/projects/HIPIFY/en/docs-6.4.2/index.html">HIPIFY</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/HIPIFY/en/docs-6.4.3/index.html">HIPIFY</a></td>
                 <td>19.0.0</td>
                 <td><a href="https://github.com/ROCm/HIPIFY/"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/ROCdbgapi/en/docs-6.4.2/index.html">ROCdbgapi</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/ROCdbgapi/en/docs-6.4.3/index.html">ROCdbgapi</a></td>
                 <td>0.77.2</td>
                 <td><a href="https://github.com/ROCm/ROCdbgapi/"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/ROCmCMakeBuildTools/en/docs-6.4.2/index.html">ROCm CMake</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/ROCmCMakeBuildTools/en/docs-6.4.3/index.html">ROCm CMake</a></td>
                 <td>0.14.0</td>
                 <td><a href="https://github.com/ROCm/rocm-cmake/"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/ROCgdb/en/docs-6.4.2/index.html">ROCm Debugger (ROCgdb)</a>
+                <td><a href="https://rocm.docs.amd.com/projects/ROCgdb/en/docs-6.4.3/index.html">ROCm Debugger (ROCgdb)</a>
                 </td>
                 <td>15.2</td>
                 <td><a href="https://github.com/ROCm/ROCgdb/"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/rocr_debug_agent/en/docs-6.4.2/index.html">ROCr Debug Agent</a>
+                <td><a href="https://rocm.docs.amd.com/projects/rocr_debug_agent/en/docs-6.4.3/index.html">ROCr Debug Agent</a>
                 </td>
                 <td>2.0.4</td>
                 <td><a href="https://github.com/ROCm/rocr_debug_agent/"><i
@@ -405,13 +372,13 @@ Click {fab}`github` to go to the component's source code on GitHub.
         <tbody class="rocm-components-compilers tbody-reverse-zebra">
             <tr>
                 <th rowspan="2" colspan="2">Compilers</th>
-                <td><a href="https://rocm.docs.amd.com/projects/HIPCC/en/docs-6.4.2/index.html">HIPCC</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/HIPCC/en/docs-6.4.3/index.html">HIPCC</a></td>
                 <td>1.1.1</td>
                 <td><a href="https://github.com/ROCm/llvm-project/tree/amd-staging/amd/hipcc"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/llvm-project/en/docs-6.4.2/index.html">llvm-project</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/llvm-project/en/docs-6.4.3/index.html">llvm-project</a></td>
                 <td>19.0.0</td>
                 <td><a href="https://github.com/ROCm/llvm-project/"><i
                             class="fab fa-github fa-lg"></i></a></td>
@@ -420,12 +387,12 @@ Click {fab}`github` to go to the component's source code on GitHub.
         <tbody class="rocm-components-runtimes tbody-reverse-zebra">
             <tr>
                 <th rowspan="2" colspan="2">Runtimes</th>
-                <td><a href="https://rocm.docs.amd.com/projects/HIP/en/docs-6.4.2/index.html">HIP</a></td>
-                <td>6.4.1&nbsp;&Rightarrow;&nbsp;<a href="#hip-6-4-2">6.4.2</td>
+                <td><a href="https://rocm.docs.amd.com/projects/HIP/en/docs-6.4.3/index.html">HIP</a></td>
+                <td>6.4.3</td>
                 <td><a href="https://github.com/ROCm/HIP/"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
             <tr>
-                <td><a href="https://rocm.docs.amd.com/projects/ROCR-Runtime/en/docs-6.4.2/index.html">ROCr Runtime</a></td>
+                <td><a href="https://rocm.docs.amd.com/projects/ROCR-Runtime/en/docs-6.4.3/index.html">ROCr Runtime</a></td>
                 <td>1.15.0</td>
                 <td><a href="https://github.com/ROCm/ROCR-Runtime/"><i class="fab fa-github fa-lg"></i></a></td>
             </tr>
@@ -441,179 +408,21 @@ The following sections describe key changes to ROCm components.
 For a historical overview of ROCm component updates, see the {doc}`ROCm consolidated changelog </release/changelog>`.
 ```
 
-### **AMD SMI** (25.5.1)
+### **ROCm SMI** (7.7.0)
 
 #### Added
 
-- Compute Unit Occupancy information per process.
-
 - Support for getting the GPU Board voltage.
 
-- New firmware PLDM_BUNDLE. `amd-smi firmware` can now show the PLDM Bundle on supported systems.
-
-- `amd-smi ras --afid --cper-file <file_path>` to decode CPER records.
-
-#### Changed
-
-- Padded `asic_serial` in `amdsmi_get_asic_info` with 0s.
-
-- Renamed field `COMPUTE_PARTITION` to `ACCELERATOR_PARTITION` in CLI call `amd-smi --partition`.
-
-#### Resolved issues
-
-- Corrected VRAM memory calculation in `amdsmi_get_gpu_process_list`. Previously, the VRAM memory usage reported by `amdsmi_get_gpu_process_list` was inaccurate and was calculated using KB instead of KiB.
-
 ```{note}
-See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-6.4/CHANGELOG.md) for details, examples, and in-depth descriptions.
+See the full [ROCm SMI changelog](https://github.com/ROCm/rocm_smi_lib/blob/release/rocm-rel-6.4/CHANGELOG.md) for details, examples, and in-depth descriptions.
 ```
 
-### **HIP** (6.4.2)
-
-#### Added
-
-* HIP API implementation for `hipEventRecordWithFlags`, records an event in the specified stream with flags.
-* Support for the pointer attribute `HIP_POINTER_ATTRIBUTE_CONTEXT`.
-* Support for the flags `hipEventWaitDefault` and `hipEventWaitExternal`.
-
-#### Optimized
-
-* Improved implementation in `hipEventSynchronize`, HIP runtime now makes internal callbacks as non-blocking operations to improve performance.
-
-#### Resolved issues
-
-* Issue of dependency on `libgcc-s1` during rocm-dev install on Debian Buster. HIP runtime removed this Debian package dependency, and uses `libgcc1` instead for this distros.
-* Building issue for `COMGR` dynamic load on Fedora and other Distros. HIP runtime now doesn't link against `libamd_comgr.so`.
-* Failure in the API `hipStreamDestroy`, when stream type is `hipStreamLegacy`. The API now returns error code `hipErrorInvalidResourceHandle` on this condition.
-* Kernel launch errors, such as `shared object initialization failed`, `invalid device function` or `kernel execution failure`. HIP runtime now loads `COMGR` properly considering the file with its name and mapped image.
-* Memory access fault in some applications. HIP runtime fixed offset accumulation in memory address.
-* The memory leak in virtual memory management (VMM). HIP runtime now uses the size of handle for allocated memory range instead of actual size for physical memory, which fixed the issue of address clash with VMM.
-* Large memory allocation issue. HIP runtime now checks GPU video RAM and system RAM properly and sets size limits during memory allocation either on the host or the GPU device.
-* Support of `hipDeviceMallocContiguous` flags in `hipExtMallocWithFlags()`. It now enables `HSA_AMD_MEMORY_POOL_CONTIGUOUS_FLAG` in the memory pool allocation on GPU device.
-* Radom memory segmentation fault in handling `GraphExec` object release and `hipDeviceSyncronization`. HIP runtime now uses internal device synchronize function in `__hipUnregisterFatBinary`. 
-
-### **hipBLASLt** (0.12.1)
-
-#### Added
-
-* Support for gfx1151 on Linux, complementing the previous support in the HIP SDK for Windows.
-
-### **RCCL** (2.22.3)
-
-#### Added
-
-* Added support for the LL128 protocol on gfx942.
-
-### **rocBLAS** (4.4.1)
-
-#### Resolved issues
-
-* rocBLAS might have failed to produce correct results for cherk/zherk on gfx90a/gfx942 with problem sizes k > 500 due to the imaginary portion on the C matrix diagonal not being zeros. rocBLAS now zeros the imaginary portion.
-
-### **ROCm Compute Profiler** (3.1.1)
-
-#### Added
-
-* 8-bit floating point (FP8) metrics support for AMD Instinct MI300 GPUs.
-* Additional data types for roofline: FP8, FP16, BF16, FP32, FP64, I8, I32, I64 (dependent on the GPU architecture).
-* Data type selection option ``--roofline-data-type / -R`` for roofline profiling. The default data type is FP32.
-
-#### Changed
-
-* Changed dependency from `rocm-smi` to `amd-smi`.
-
-#### Resolved issues
-
-* Fixed a crash related to Agent ID caused by the new format of the `rocprofv3` output CSV file.
-
-### **ROCm Systems Profiler** (1.0.2)
-
-#### Optimized
-
-* Improved readability of the OpenMP target offload traces by showing on a single Perfetto track.
-
-#### Resolved issues
-
-* Fixed the file path to the script that merges Perfetto files from multi-process MPI runs. The script has also been renamed from `merge-multiprocess-output.sh` to `rocprof-sys-merge-output.sh`.
-
-### **ROCm Validation Suite** (1.1.0)
-
-#### Added
-
-* NPS2/DPX and NPS4/CPX partition modes support for AMD Instinct MI300X.
-
-### **rocPRIM** (3.4.1)
-
-#### Upcoming changes
-
-* Changes to the template parameters of warp and block algorithms will be made in an upcoming release.
-* Due to an upcoming compiler change, the following symbols related to warp size have been marked as deprecated and will be removed in an upcoming major release:
-    * `rocprim::device_warp_size()`. This has been replaced by `rocprim::arch::wavefront::min_size()` and `rocprim::arch::wavefront::max_size()` for compile-time constants. Use these when allocating global or shared memory. For run-time constants, use `rocprim::arch::wavefront::size()`.
-  * `rocprim::warp_size()`
-  * `ROCPRIM_WAVEFRONT_SIZE`
-
-* The default scan accumulator types for device-level scan algorithms will be changed in an upcoming release, resulting in a breaking change. Previously, the default accumulator type was set to the input type for the inclusive scans and to the initial value type for the exclusive scans. This could lead to unexpected overflow if the input or initial type was smaller than the output type when the accumulator type wasn't explicitly set using the `AccType` template parameter. The new default accumulator types will be set to the type that results when the input or initial value type is applied to the scan operator.  
-
-    The following is the complete list of affected functions and how their default accumulator types are changing:
-    
-    * `rocprim::inclusive_scan`
-        * current default: `class AccType = typename std::iterator_traits<InputIterator>::value_type>`
-        * future default: `class AccType = rocprim::invoke_result_binary_op_t<typename std::iterator_traits<InputIterator>::value_type, BinaryFunction>`
-    * `rocprim::deterministic_inclusive_scan`
-        * current default: `class AccType = typename std::iterator_traits<InputIterator>::value_type>`
-        * future default: `class AccType = rocprim::invoke_result_binary_op_t<typename std::iterator_traits<InputIterator>::value_type, BinaryFunction>`
-    * `rocprim::exclusive_scan`
-        * current default: `class AccType = detail::input_type_t<InitValueType>>`
-        * future default: `class AccType = rocprim::invoke_result_binary_op_t<rocprim::detail::input_type_t<InitValueType>, BinaryFunction>`
-    * `rocprim::deterministic_exclusive_scan`
-        * current default: `class AccType = detail::input_type_t<InitValueType>>`
-        * future default: `class AccType = rocprim::invoke_result_binary_op_t<rocprim::detail::input_type_t<InitValueType>, BinaryFunction>`
-
-* `rocprim::load_cs` and `rocprim::store_cs` are deprecated and will be removed in an upcoming release. Alternatively, you can use `rocprim::load_nontemporal` and `rocprim::store_nontemporal` to load and store values in specific conditions (like bypassing the cache) for `rocprim::thread_load` and `rocprim::thread_store`.
-
-### **rocSHMEM** (2.0.1)
-
-#### Resolved issues
-
-* Incorrect output for `rocshmem_ctx_my_pe` and `rocshmem_ctx_n_pes`.
-* Multi-team errors by providing team specific buffers in `rocshmem_ctx_wg_team_sync`.
-* Missing implementation of `rocshmem_g` for IPC conduit.
-
-### **rocSOLVER** (3.28.2)
-
-#### Added
-
-* Hybrid computation support for existing routines, such as STERF.
-* SVD for general matrices based on Cuppen's Divide and Conquer algorithm:
-    - GESDD (with batched and strided\_batched versions)
-
-#### Optimized
-
-* Reduced the device memory requirements for STEDC, SYEVD/HEEVD, and SYGVD/HEGVD.
-* Improved the performance of STEDC and divide and conquer Eigensolvers.
-* Improved the performance of SYTRD, the initial step of the Eigensolvers that start with the tridiagonalization of the input matrix.
-
 ## ROCm known issues
 
 ROCm known issues are noted on {fab}`github` [GitHub](https://github.com/ROCm/ROCm/labels/Verified%20Issue). For known
 issues related to individual components, review the [Detailed component changes](#detailed-component-changes).
 
-## ROCm resolved issues
-
-The following are previously known issues resolved in this release. For resolved issues related to
-individual components, review the [Detailed component changes](#detailed-component-changes).
-
-### AMD SMI CLI: CPER entries not dumped continuously when using follow flag
-
-An issue where CPER entries were not streamed continuously as intended when using the `--follow` flag with `amd-smi ras --cper` has been resolved. See [GitHub issue #4768](https://github.com/ROCm/ROCm/issues/4768).
-
-### Instinct MI300X reports incorrect raw GPU timestamps
-
-An issue where the command processor firmware reported incorrect raw GPU timestamps on MI300X accelerators has been resolved. See [GitHub issue #4079](https://github.com/ROCm/ROCm/issues/4079).
-
-### MIOpen generates incorrect results for particular input with FP32 data type
-
-An issue where MIOpen generated incorrect results on the `conv2dbackward` function for a particular input with 32-bit floating point (FP32) data types has been resolved. The issue was only specific to FP32 data types with 2 * 2 kernel size and dilation 2 * 1. See [GitHub issue #4606](https://github.com/ROCm/ROCm/issues/4606). 
-
 ## ROCm upcoming changes
 
 The following changes to the ROCm software stack are anticipated for future releases.
@@ -649,10 +458,10 @@ and will be disabled in a future release.
 
 * The `__AMDGCN_WAVEFRONT_SIZE__` macro and `__AMDGCN_WAVEFRONT_SIZE` alias will be removed in an upcoming release.
   It is recommended to remove any use of this macro. For more information, see
-  [AMDGPU support](https://rocm.docs.amd.com/projects/llvm-project/en/docs-6.4.2/LLVM/clang/html/AMDGPUSupport.html).
+  [AMDGPU support](https://rocm.docs.amd.com/projects/llvm-project/en/docs-6.4.3/LLVM/clang/html/AMDGPUSupport.html).
 * `warpSize` will only be available as a non-`constexpr` variable. Where required,
   the wavefront size should be queried via the `warpSize` variable in device code,
-  or via `hipGetDeviceProperties` in host code. Neither of these will result in a compile-time constant. For more information, see [warpSize](https://rocm.docs.amd.com/projects/HIP/en/docs-6.4.2/how-to/hip_cpp_language_extensions.html#warpsize).
+  or via `hipGetDeviceProperties` in host code. Neither of these will result in a compile-time constant. For more information, see [warpSize](https://rocm.docs.amd.com/projects/HIP/en/docs-6.4.3/how-to/hip_cpp_language_extensions.html#warpsize).
 * For cases where compile-time evaluation of the wavefront size cannot be avoided,
   uses of `__AMDGCN_WAVEFRONT_SIZE`, `__AMDGCN_WAVEFRONT_SIZE__`, or `warpSize`
   can be replaced with a user-defined macro or `constexpr` variable with the wavefront

docs/compatibility/compatibility-matrix-historical-6.0.csv

@@ -1,129 +1,131 @@
-ROCm Version,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0, 6.1.5, 6.1.2, 6.1.1, 6.1.0, 6.0.2, 6.0.0
-      :ref:`Operating systems & kernels <OS-kernel-versions>`,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,"Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04",Ubuntu 24.04,,,,,,
-      ,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,"Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3, 22.04.2","Ubuntu 22.04.4, 22.04.3, 22.04.2"
-      ,,,,,,,,,,,,"Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5"
-      ,"RHEL 9.6, 9.4","RHEL 9.6, 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.3, 9.2","RHEL 9.3, 9.2"
-      ,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,"RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8"
-      ,"SLES 15 SP7, SP6",SLES 15 SP6,SLES 15 SP6,"SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4"
-      ,,,,,,,,,,,,,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9
-      ,"Oracle Linux 9, 8 [#mi300x-past-60]_","Oracle Linux 9, 8 [#mi300x-past-60]_","Oracle Linux 9, 8 [#mi300x-past-60]_",Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,,,
-      ,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,,,,,,,,,,,
-      ,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,,,,,,,,,,,,
-      ,.. _architecture-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3
-      ,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2
-      ,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA
-      ,RDNA4,RDNA4,,,,,,,,,,,,,,,
-      ,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3
-      ,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2
-      ,.. _gpu-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`GPU / LLVM target <rocm-install-on-linux:reference/system-requirements>`,gfx1201 [#RDNA-OS-past-60]_,gfx1201 [#RDNA-OS-past-60]_,,,,,,,,,,,,,,,
-      ,gfx1200 [#RDNA-OS-past-60]_,gfx1200 [#RDNA-OS-past-60]_,,,,,,,,,,,,,,,
-,gfx1101 [#RDNA-OS-past-60]_ [#7700XT-OS-past-60]_,gfx1101 [#RDNA-OS-past-60]_,,,,,,,,,,,,,,,
-      ,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100
-      ,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030
-      ,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942 [#mi300_624-past-60]_,gfx942 [#mi300_622-past-60]_,gfx942 [#mi300_621-past-60]_,gfx942 [#mi300_620-past-60]_, gfx942 [#mi300_612-past-60]_, gfx942 [#mi300_612-past-60]_, gfx942 [#mi300_611-past-60]_, gfx942 [#mi300_610-past-60]_, gfx942 [#mi300_602-past-60]_, gfx942 [#mi300_600-past-60]_
-      ,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a
-      ,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908
-,,,,,,,,,,,,,,,,,
-      FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13"
-      :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.14.0, 2.13.1, 2.12.1","2.14.0, 2.13.1, 2.12.1"
-      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.4.35,0.4.35,0.4.35,0.4.31,0.4.31,0.4.31,0.4.31,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
-      :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`,N/A,N/A,N/A,N/A,N/A,85f95ae,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>`,2.4.0,2.4.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.3.0.post0,N/A,N/A,N/A,N/A,N/A,N/A
-      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.2,1.2,1.2,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
-,,,,,,,,,,,,,,,,,
-      ,,,,,,,,,,,,,,,,,
-      THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      `UCC <https://github.com/ROCm/ucc>`_,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.2.0,>=1.2.0
-      `UCX <https://github.com/ROCm/ucx>`_,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1
-      ,,,,,,,,,,,,,,,,,
-      THIRD PARTY ALGORITHM,.. _thirdpartyalgorithm-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      Thrust,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
-      CUB,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
-,,,,,,,,,,,,,,,,,
-      KMD & USER SPACE [#kfd_support-past-60]_,.. _kfd-userspace-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`KMD versions <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x"
-      ,,,,,,,,,,,,,,,,,
-      ML & COMPUTER VISION,.. _mllibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`Composable Kernel <composable_kernel:index>`,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0
-      :doc:`MIGraphX <amdmigraphx:index>`,2.12.0,2.12.0,2.12.0,2.11.0,2.11.0,2.11.0,2.11.0,2.10.0,2.10.0,2.10.0,2.10.0,2.9.0,2.9.0,2.9.0,2.9.0,2.8.0,2.8.0
-      :doc:`MIOpen <miopen:index>`,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
-      :doc:`MIVisionX <mivisionx:index>`,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0
-      :doc:`rocAL <rocal:index>`,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0,2.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
-      :doc:`rocDecode <rocdecode:index>`,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,N/A,N/A
-      :doc:`rocJPEG <rocjpeg:index>`,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`rocPyDecode <rocpydecode:index>`,0.3.1,0.3.1,0.3.1,0.2.0,0.2.0,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`RPP <rpp:index>`,1.9.10,1.9.10,1.9.10,1.9.1,1.9.1,1.9.1,1.9.1,1.8.0,1.8.0,1.8.0,1.8.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0
-      ,,,,,,,,,,,,,,,,,
-      COMMUNICATION,.. _commlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`RCCL <rccl:index>`,2.22.3,2.22.3,2.22.3,2.21.5,2.21.5,2.21.5,2.21.5,2.20.5,2.20.5,2.20.5,2.20.5,2.18.6,2.18.6,2.18.6,2.18.6,2.18.3,2.18.3
-      :doc:`rocSHMEM <rocshmem:index>`,2.0.1,2.0.0,2.0.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
-      ,,,,,,,,,,,,,,,,,
-      MATH LIBS,.. _mathlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      `half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0
-      :doc:`hipBLAS <hipblas:index>`,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0
-      :doc:`hipBLASLt <hipblaslt:index>`,0.12.1,0.12.1,0.12.0,0.10.0,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.7.0,0.7.0,0.7.0,0.7.0,0.6.0,0.6.0
-      :doc:`hipFFT <hipfft:index>`,1.0.18,1.0.18,1.0.18,1.0.17,1.0.17,1.0.17,1.0.17,1.0.16,1.0.15,1.0.15,1.0.14,1.0.14,1.0.14,1.0.14,1.0.14,1.0.13,1.0.13
-      :doc:`hipfort <hipfort:index>`,0.6.0,0.6.0,0.6.0,0.5.1,0.5.1,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0
-      :doc:`hipRAND <hiprand:index>`,2.12.0,2.12.0,2.12.0,2.11.1,2.11.1,2.11.1,2.11.0,2.11.1,2.11.0,2.11.0,2.11.0,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16
-      :doc:`hipSOLVER <hipsolver:index>`,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.1,2.1.1,2.1.1,2.1.0,2.0.0,2.0.0
-      :doc:`hipSPARSE <hipsparse:index>`,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.1.1,3.1.1,3.1.1,3.1.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
-      :doc:`hipSPARSELt <hipsparselt:index>`,0.2.3,0.2.3,0.2.3,0.2.2,0.2.2,0.2.2,0.2.2,0.2.1,0.2.1,0.2.1,0.2.1,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0
-      :doc:`rocALUTION <rocalution:index>`,3.2.3,3.2.3,3.2.2,3.2.1,3.2.1,3.2.1,3.2.1,3.2.1,3.2.0,3.2.0,3.2.0,3.1.1,3.1.1,3.1.1,3.1.1,3.0.3,3.0.3
-      :doc:`rocBLAS <rocblas:index>`,4.4.1,4.4.0,4.4.0,4.3.0,4.3.0,4.3.0,4.3.0,4.2.4,4.2.1,4.2.1,4.2.0,4.1.2,4.1.2,4.1.0,4.1.0,4.0.0,4.0.0
-      :doc:`rocFFT <rocfft:index>`,1.0.32,1.0.32,1.0.32,1.0.31,1.0.31,1.0.31,1.0.31,1.0.30,1.0.29,1.0.29,1.0.28,1.0.27,1.0.27,1.0.27,1.0.26,1.0.25,1.0.23
-      :doc:`rocRAND <rocrand:index>`,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.1,3.1.0,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,2.10.17
-      :doc:`rocSOLVER <rocsolver:index>`,3.28.2,3.28.0,3.28.0,3.27.0,3.27.0,3.27.0,3.27.0,3.26.2,3.26.0,3.26.0,3.26.0,3.25.0,3.25.0,3.25.0,3.25.0,3.24.0,3.24.0
-      :doc:`rocSPARSE <rocsparse:index>`,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.0.2,3.0.2
-      :doc:`rocWMMA <rocwmma:index>`,1.7.0,1.7.0,1.7.0,1.6.0,1.6.0,1.6.0,1.6.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0
-      :doc:`Tensile <tensile:src/index>`,4.43.0,4.43.0,4.43.0,4.42.0,4.42.0,4.42.0,4.42.0,4.41.0,4.41.0,4.41.0,4.41.0,4.40.0,4.40.0,4.40.0,4.40.0,4.39.0,4.39.0
-      ,,,,,,,,,,,,,,,,,
-      PRIMITIVES,.. _primitivelibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`hipCUB <hipcub:index>`,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
-      :doc:`hipTensor <hiptensor:index>`,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0,1.3.0,1.3.0,1.2.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0
-      :doc:`rocPRIM <rocprim:index>`,3.4.1,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.2,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
-      :doc:`rocThrust <rocthrust:index>`,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.1.1,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
-      ,,,,,,,,,,,,,,,,,
-      SUPPORT LIBS,,,,,,,,,,,,,,,,,
-      `hipother <https://github.com/ROCm/hipother>`_,6.4.43483,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
-      `rocm-core <https://github.com/ROCm/rocm-core>`_,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0,6.1.5,6.1.2,6.1.1,6.1.0,6.0.2,6.0.0
-      `ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,20240607.5.7,20240607.5.7,20240607.4.05,20240607.1.4246,20240125.5.08,20240125.5.08,20240125.5.08,20240125.3.30,20231016.2.245,20231016.2.245
-      ,,,,,,,,,,,,,,,,,
-      SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`AMD SMI <amdsmi:index>`,25.5.1,25.4.2,25.3.0,24.7.1,24.7.1,24.7.1,24.7.1,24.6.3,24.6.3,24.6.3,24.6.2,24.5.1,24.5.1,24.5.1,24.4.1,23.4.2,23.4.2
-      :doc:`ROCm Data Center Tool <rdc:index>`,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0
-      :doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
-      :doc:`ROCm SMI <rocm_smi_lib:index>`,7.5.0,7.5.0,7.5.0,7.4.0,7.4.0,7.4.0,7.4.0,7.3.0,7.3.0,7.3.0,7.3.0,7.2.0,7.2.0,7.0.0,7.0.0,6.0.2,6.0.0
-      :doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.0.60204,1.0.60202,1.0.60201,1.0.60200,1.0.60105,1.0.60102,1.0.60101,1.0.60100,1.0.60002,1.0.60000
-      ,,,,,,,,,,,,,,,,,
-      PERFORMANCE TOOLS,,,,,,,,,,,,,,,,,
-      :doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0
-      :doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.1.1,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.0.1,2.0.1,2.0.1,2.0.1,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.0.2,1.0.1,1.0.0,0.1.2,0.1.1,0.1.0,0.1.0,1.11.2,1.11.2,1.11.2,1.11.2,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`ROCProfiler <rocprofiler:index>`,2.0.60402,2.0.60401,2.0.60400,2.0.60303,2.0.60302,2.0.60301,2.0.60300,2.0.60204,2.0.60202,2.0.60201,2.0.60200,2.0.60105,2.0.60102,2.0.60101,2.0.60100,2.0.60002,2.0.60000
-      :doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,N/A,N/A,N/A,N/A,N/A,N/A
-      :doc:`ROCTracer <roctracer:index>`,4.1.60402,4.1.60401,4.1.60400,4.1.60303,4.1.60302,4.1.60301,4.1.60300,4.1.60204,4.1.60202,4.1.60201,4.1.60200,4.1.60105,4.1.60102,4.1.60101,4.1.60100,4.1.60002,4.1.60000
-      ,,,,,,,,,,,,,,,,,
-      DEVELOPMENT TOOLS,,,,,,,,,,,,,,,,,
-      :doc:`HIPIFY <hipify:index>`,19.0.0,19.0.0,19.0.0,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-      :doc:`ROCm CMake <rocmcmakebuildtools:index>`,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.13.0,0.13.0,0.13.0,0.13.0,0.12.0,0.12.0,0.12.0,0.12.0,0.11.0,0.11.0
-      :doc:`ROCdbgapi <rocdbgapi:index>`,0.77.2,0.77.2,0.77.2,0.77.0,0.77.0,0.77.0,0.77.0,0.76.0,0.76.0,0.76.0,0.76.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0
-      :doc:`ROCm Debugger (ROCgdb) <rocgdb:index>`,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,14.2.0,14.2.0,14.2.0,14.2.0,14.1.0,14.1.0,14.1.0,14.1.0,13.2.0,13.2.0
-      `rocprofiler-register <https://github.com/ROCm/rocprofiler-register>`_,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.3.0,0.3.0,0.3.0,0.3.0,N/A,N/A
-      :doc:`ROCr Debug Agent <rocr_debug_agent:index>`,2.0.4,2.0.4,2.0.4,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3
-      ,,,,,,,,,,,,,,,,,
-      COMPILERS,.. _compilers-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      `clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0
-      :doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
-      `Flang <https://github.com/ROCm/flang>`_,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-      :doc:`llvm-project <llvm-project:index>`,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-      `OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-,,,,,,,,,,,,,,,,,
-      RUNTIMES,.. _runtime-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,
-      :doc:`AMD CLR <hip:understand/amd_clr>`,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
-      :doc:`HIP <hip:index>`,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
-      `OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0
-      :doc:`ROCr Runtime <rocr-runtime:index>`,1.15.0,1.15.0,1.15.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.13.0,1.13.0,1.13.0,1.13.0,1.13.0,1.12.0,1.12.0
+ROCm Version,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0, 6.1.5, 6.1.2, 6.1.1, 6.1.0, 6.0.2, 6.0.0
+      :ref:`Operating systems & kernels <OS-kernel-versions>`,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,"Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04",Ubuntu 24.04,,,,,,
+      ,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,"Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3, 22.04.2","Ubuntu 22.04.4, 22.04.3, 22.04.2"
+      ,,,,,,,,,,,,,"Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5"
+      ,"RHEL 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.6, 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.3, 9.2","RHEL 9.3, 9.2"
+      ,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,"RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8"
+      ,"SLES 15 SP7, SP6","SLES 15 SP7, SP6",SLES 15 SP6,SLES 15 SP6,"SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4"
+      ,,,,,,,,,,,,,,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9
+      ,"Oracle Linux 9, 8 [#mi300x-past-60]_","Oracle Linux 9, 8 [#mi300x-past-60]_","Oracle Linux 9, 8 [#mi300x-past-60]_","Oracle Linux 9, 8 [#mi300x-past-60]_",Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.10 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,Oracle Linux 8.9 [#mi300x-past-60]_,,,
+      ,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-past-60]_,,,,,,,,,,,
+      ,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,Azure Linux 3.0 [#mi300x-past-60]_,,,,,,,,,,,,
+      ,.. _architecture-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3
+      ,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2
+      ,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA
+      ,RDNA4,RDNA4,RDNA4,,,,,,,,,,,,,,,
+      ,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3
+      ,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2
+      ,.. _gpu-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`GPU / LLVM target <rocm-install-on-linux:reference/system-requirements>`,gfx1201 [#RDNA-OS-past-60]_,gfx1201 [#RDNA-OS-past-60]_,gfx1201 [#RDNA-OS-past-60]_,,,,,,,,,,,,,,,
+      ,gfx1200 [#RDNA-OS-past-60]_,gfx1200 [#RDNA-OS-past-60]_,gfx1200 [#RDNA-OS-past-60]_,,,,,,,,,,,,,,,
+,gfx1101 [#RDNA-OS-past-60]_ [#7700XT-OS-past-60]_,gfx1101 [#RDNA-OS-past-60]_ [#7700XT-OS-past-60]_,gfx1101 [#RDNA-OS-past-60]_,,,,,,,,,,,,,,,
+      ,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100
+      ,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030
+      ,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942 [#mi300_624-past-60]_,gfx942 [#mi300_622-past-60]_,gfx942 [#mi300_621-past-60]_,gfx942 [#mi300_620-past-60]_, gfx942 [#mi300_612-past-60]_, gfx942 [#mi300_612-past-60]_, gfx942 [#mi300_611-past-60]_, gfx942 [#mi300_610-past-60]_, gfx942 [#mi300_602-past-60]_, gfx942 [#mi300_600-past-60]_
+      ,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a
+      ,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908
+,,,,,,,,,,,,,,,,,,
+      FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13"
+      :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.14.0, 2.13.1, 2.12.1","2.14.0, 2.13.1, 2.12.1"
+      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.4.35,0.4.35,0.4.35,0.4.35,0.4.31,0.4.31,0.4.31,0.4.31,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
+      :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.3.0.post0,N/A,N/A,N/A,N/A,N/A
+      :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>` [#stanford-megatron-lm_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,85f95ae,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat]_,N/A,N/A,N/A,2.4.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,
+      :doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>` [#megablocks_compat]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.7.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`Taichi <../compatibility/ml-compatibility/taichi-compatibility>` [#taichi_compat]_,N/A,N/A,N/A,N/A,N/A,1.8.0b1,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
+      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.2,1.2,1.2,1.2,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
+,,,,,,,,,,,,,,,,,,
+      ,,,,,,,,,,,,,,,,,,
+      THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      `UCC <https://github.com/ROCm/ucc>`_,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.2.0,>=1.2.0
+      `UCX <https://github.com/ROCm/ucx>`_,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1
+      ,,,,,,,,,,,,,,,,,,
+      THIRD PARTY ALGORITHM,.. _thirdpartyalgorithm-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      Thrust,2.5.0,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
+      CUB,2.5.0,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
+,,,,,,,,,,,,,,,,,,
+      KMD & USER SPACE [#kfd_support-past-60]_,.. _kfd-userspace-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`KMD versions <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x"
+      ,,,,,,,,,,,,,,,,,,
+      ML & COMPUTER VISION,.. _mllibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`Composable Kernel <composable_kernel:index>`,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0
+      :doc:`MIGraphX <amdmigraphx:index>`,2.12.0,2.12.0,2.12.0,2.12.0,2.11.0,2.11.0,2.11.0,2.11.0,2.10.0,2.10.0,2.10.0,2.10.0,2.9.0,2.9.0,2.9.0,2.9.0,2.8.0,2.8.0
+      :doc:`MIOpen <miopen:index>`,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
+      :doc:`MIVisionX <mivisionx:index>`,3.2.0,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0
+      :doc:`rocAL <rocal:index>`,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0,2.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
+      :doc:`rocDecode <rocdecode:index>`,0.10.0,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,N/A,N/A
+      :doc:`rocJPEG <rocjpeg:index>`,0.8.0,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`rocPyDecode <rocpydecode:index>`,0.3.1,0.3.1,0.3.1,0.3.1,0.2.0,0.2.0,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`RPP <rpp:index>`,1.9.10,1.9.10,1.9.10,1.9.10,1.9.1,1.9.1,1.9.1,1.9.1,1.8.0,1.8.0,1.8.0,1.8.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0
+      ,,,,,,,,,,,,,,,,,,
+      COMMUNICATION,.. _commlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`RCCL <rccl:index>`,2.22.3,2.22.3,2.22.3,2.22.3,2.21.5,2.21.5,2.21.5,2.21.5,2.20.5,2.20.5,2.20.5,2.20.5,2.18.6,2.18.6,2.18.6,2.18.6,2.18.3,2.18.3
+      :doc:`rocSHMEM <rocshmem:index>`,2.0.1,2.0.1,2.0.0,2.0.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
+      ,,,,,,,,,,,,,,,,,,
+      MATH LIBS,.. _mathlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      `half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0
+      :doc:`hipBLAS <hipblas:index>`,2.4.0,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0
+      :doc:`hipBLASLt <hipblaslt:index>`,0.12.1,0.12.1,0.12.1,0.12.0,0.10.0,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.7.0,0.7.0,0.7.0,0.7.0,0.6.0,0.6.0
+      :doc:`hipFFT <hipfft:index>`,1.0.18,1.0.18,1.0.18,1.0.18,1.0.17,1.0.17,1.0.17,1.0.17,1.0.16,1.0.15,1.0.15,1.0.14,1.0.14,1.0.14,1.0.14,1.0.14,1.0.13,1.0.13
+      :doc:`hipfort <hipfort:index>`,0.6.0,0.6.0,0.6.0,0.6.0,0.5.1,0.5.1,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0
+      :doc:`hipRAND <hiprand:index>`,2.12.0,2.12.0,2.12.0,2.12.0,2.11.1,2.11.1,2.11.1,2.11.0,2.11.1,2.11.0,2.11.0,2.11.0,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16
+      :doc:`hipSOLVER <hipsolver:index>`,2.4.0,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.1,2.1.1,2.1.1,2.1.0,2.0.0,2.0.0
+      :doc:`hipSPARSE <hipsparse:index>`,3.2.0,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.1.1,3.1.1,3.1.1,3.1.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
+      :doc:`hipSPARSELt <hipsparselt:index>`,0.2.3,0.2.3,0.2.3,0.2.3,0.2.2,0.2.2,0.2.2,0.2.2,0.2.1,0.2.1,0.2.1,0.2.1,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0
+      :doc:`rocALUTION <rocalution:index>`,3.2.3,3.2.3,3.2.3,3.2.2,3.2.1,3.2.1,3.2.1,3.2.1,3.2.1,3.2.0,3.2.0,3.2.0,3.1.1,3.1.1,3.1.1,3.1.1,3.0.3,3.0.3
+      :doc:`rocBLAS <rocblas:index>`,4.4.1,4.4.1,4.4.0,4.4.0,4.3.0,4.3.0,4.3.0,4.3.0,4.2.4,4.2.1,4.2.1,4.2.0,4.1.2,4.1.2,4.1.0,4.1.0,4.0.0,4.0.0
+      :doc:`rocFFT <rocfft:index>`,1.0.32,1.0.32,1.0.32,1.0.32,1.0.31,1.0.31,1.0.31,1.0.31,1.0.30,1.0.29,1.0.29,1.0.28,1.0.27,1.0.27,1.0.27,1.0.26,1.0.25,1.0.23
+      :doc:`rocRAND <rocrand:index>`,3.3.0,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.1,3.1.0,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,2.10.17
+      :doc:`rocSOLVER <rocsolver:index>`,3.28.2,3.28.2,3.28.0,3.28.0,3.27.0,3.27.0,3.27.0,3.27.0,3.26.2,3.26.0,3.26.0,3.26.0,3.25.0,3.25.0,3.25.0,3.25.0,3.24.0,3.24.0
+      :doc:`rocSPARSE <rocsparse:index>`,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.0.2,3.0.2
+      :doc:`rocWMMA <rocwmma:index>`,1.7.0,1.7.0,1.7.0,1.7.0,1.6.0,1.6.0,1.6.0,1.6.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0
+      :doc:`Tensile <tensile:src/index>`,4.43.0,4.43.0,4.43.0,4.43.0,4.42.0,4.42.0,4.42.0,4.42.0,4.41.0,4.41.0,4.41.0,4.41.0,4.40.0,4.40.0,4.40.0,4.40.0,4.39.0,4.39.0
+      ,,,,,,,,,,,,,,,,,,
+      PRIMITIVES,.. _primitivelibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`hipCUB <hipcub:index>`,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
+      :doc:`hipTensor <hiptensor:index>`,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0,1.3.0,1.3.0,1.2.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0
+      :doc:`rocPRIM <rocprim:index>`,3.4.1,3.4.1,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.2,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
+      :doc:`rocThrust <rocthrust:index>`,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.1.1,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
+      ,,,,,,,,,,,,,,,,,,
+      SUPPORT LIBS,,,,,,,,,,,,,,,,,,
+      `hipother <https://github.com/ROCm/hipother>`_,6.4.43483,6.4.43483,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
+      `rocm-core <https://github.com/ROCm/rocm-core>`_,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0,6.1.5,6.1.2,6.1.1,6.1.0,6.0.2,6.0.0
+      `ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,20240607.5.7,20240607.5.7,20240607.4.05,20240607.1.4246,20240125.5.08,20240125.5.08,20240125.5.08,20240125.3.30,20231016.2.245,20231016.2.245
+      ,,,,,,,,,,,,,,,,,,
+      SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`AMD SMI <amdsmi:index>`,25.5.1,25.5.1,25.4.2,25.3.0,24.7.1,24.7.1,24.7.1,24.7.1,24.6.3,24.6.3,24.6.3,24.6.2,24.5.1,24.5.1,24.5.1,24.4.1,23.4.2,23.4.2
+      :doc:`ROCm Data Center Tool <rdc:index>`,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0
+      :doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
+      :doc:`ROCm SMI <rocm_smi_lib:index>`,7.7.0,7.5.0,7.5.0,7.5.0,7.4.0,7.4.0,7.4.0,7.4.0,7.3.0,7.3.0,7.3.0,7.3.0,7.2.0,7.2.0,7.0.0,7.0.0,6.0.2,6.0.0
+      :doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.0.60204,1.0.60202,1.0.60201,1.0.60200,1.0.60105,1.0.60102,1.0.60101,1.0.60100,1.0.60002,1.0.60000
+      ,,,,,,,,,,,,,,,,,,
+      PERFORMANCE TOOLS,,,,,,,,,,,,,,,,,,
+      :doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0
+      :doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.1.1,3.1.1,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.0.1,2.0.1,2.0.1,2.0.1,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.0.2,1.0.2,1.0.1,1.0.0,0.1.2,0.1.1,0.1.0,0.1.0,1.11.2,1.11.2,1.11.2,1.11.2,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`ROCProfiler <rocprofiler:index>`,2.0.60403,2.0.60402,2.0.60401,2.0.60400,2.0.60303,2.0.60302,2.0.60301,2.0.60300,2.0.60204,2.0.60202,2.0.60201,2.0.60200,2.0.60105,2.0.60102,2.0.60101,2.0.60100,2.0.60002,2.0.60000
+      :doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`ROCTracer <roctracer:index>`,4.1.60403,4.1.60402,4.1.60401,4.1.60400,4.1.60303,4.1.60302,4.1.60301,4.1.60300,4.1.60204,4.1.60202,4.1.60201,4.1.60200,4.1.60105,4.1.60102,4.1.60101,4.1.60100,4.1.60002,4.1.60000
+      ,,,,,,,,,,,,,,,,,,
+      DEVELOPMENT TOOLS,,,,,,,,,,,,,,,,,,
+      :doc:`HIPIFY <hipify:index>`,19.0.0,19.0.0,19.0.0,19.0.0,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+      :doc:`ROCm CMake <rocmcmakebuildtools:index>`,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.13.0,0.13.0,0.13.0,0.13.0,0.12.0,0.12.0,0.12.0,0.12.0,0.11.0,0.11.0
+      :doc:`ROCdbgapi <rocdbgapi:index>`,0.77.2,0.77.2,0.77.2,0.77.2,0.77.0,0.77.0,0.77.0,0.77.0,0.76.0,0.76.0,0.76.0,0.76.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0
+      :doc:`ROCm Debugger (ROCgdb) <rocgdb:index>`,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,14.2.0,14.2.0,14.2.0,14.2.0,14.1.0,14.1.0,14.1.0,14.1.0,13.2.0,13.2.0
+      `rocprofiler-register <https://github.com/ROCm/rocprofiler-register>`_,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.3.0,0.3.0,0.3.0,0.3.0,N/A,N/A
+      :doc:`ROCr Debug Agent <rocr_debug_agent:index>`,2.0.4,2.0.4,2.0.4,2.0.4,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3
+      ,,,,,,,,,,,,,,,,,,
+      COMPILERS,.. _compilers-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      `clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0
+      :doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
+      `Flang <https://github.com/ROCm/flang>`_,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+      :doc:`llvm-project <llvm-project:index>`,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+      `OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+,,,,,,,,,,,,,,,,,,
+      RUNTIMES,.. _runtime-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,
+      :doc:`AMD CLR <hip:understand/amd_clr>`,6.4.43484,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
+      :doc:`HIP <hip:index>`,6.4.43484,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
+      `OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0
+      :doc:`ROCr Runtime <rocr-runtime:index>`,1.15.0,1.15.0,1.15.0,1.15.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.13.0,1.13.0,1.13.0,1.13.0,1.13.0,1.12.0,1.12.0

docs/compatibility/compatibility-matrix.rst

@@ -23,14 +23,14 @@ compatibility and system requirements.
 .. container:: format-big-table
 
   .. csv-table::
-      :header: "ROCm Version", "6.4.2", "6.4.1", "6.3.0"
+      :header: "ROCm Version", "6.4.3", "6.4.2", "6.3.0"
       :stub-columns: 1
 
       :ref:`Operating systems & kernels <OS-kernel-versions>`,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2
       ,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5
-      ,"RHEL 9.6, 9.4","RHEL 9.6, 9.5, 9.4","RHEL 9.5, 9.4"
+      ,"RHEL 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.5, 9.4"
       ,RHEL 8.10,RHEL 8.10,RHEL 8.10
-      ,"SLES 15 SP7, SP6",SLES 15 SP6,"SLES 15 SP6, SP5"
+      ,"SLES 15 SP7, SP6","SLES 15 SP7, SP6","SLES 15 SP6, SP5"
       ,"Oracle Linux 9, 8 [#mi300x]_","Oracle Linux 9, 8 [#mi300x]_",Oracle Linux 8.10 [#mi300x]_
       ,Debian 12 [#single-node]_,Debian 12 [#single-node]_,
       ,Azure Linux 3.0 [#mi300x]_,Azure Linux 3.0 [#mi300x]_,
@@ -44,7 +44,7 @@ compatibility and system requirements.
       ,.. _gpu-support-compatibility-matrix:,,
       :doc:`GPU / LLVM target <rocm-install-on-linux:reference/system-requirements>`,gfx1201 [#RDNA-OS]_,gfx1201 [#RDNA-OS]_,
       ,gfx1200 [#RDNA-OS]_,gfx1200 [#RDNA-OS]_,
-      ,gfx1101 [#RDNA-OS]_ [#7700XT-OS]_,gfx1101 [#RDNA-OS]_,
+      ,gfx1101 [#RDNA-OS]_ [#7700XT-OS]_,gfx1101 [#RDNA-OS]_ [#7700XT-OS]_,
       ,gfx1100,gfx1100,gfx1100
       ,gfx1030,gfx1030,gfx1030
       ,gfx942,gfx942,gfx942
@@ -54,9 +54,9 @@ compatibility and system requirements.
       FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix:,,
       :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 2.1, 2.0, 1.13"
       :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.17.0, 2.16.2, 2.15.1"
-      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.4.35,0.4.35,0.4.31  
+      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.4.35,0.4.35,0.4.31
       :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`,N/A,N/A,85f95ae
-      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>`,2.4.0,2.4.0,N/A
+      :doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>`,N/A,N/A,0.7.0
       `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.2,1.2,1.17.3
       ,,,
       THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix:,,
@@ -83,7 +83,7 @@ compatibility and system requirements.
       ,,,
       COMMUNICATION,.. _commlibs-support-compatibility-matrix:,,
       :doc:`RCCL <rccl:index>`,2.22.3,2.22.3,2.21.5
-      :doc:`rocSHMEM <rocshmem:index>`,2.0.1,2.0.0,N/A
+      :doc:`rocSHMEM <rocshmem:index>`,2.0.1,2.0.1,N/A
       ,,,
       MATH LIBS,.. _mathlibs-support-compatibility-matrix:,,
       `half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0
@@ -96,10 +96,10 @@ compatibility and system requirements.
       :doc:`hipSPARSE <hipsparse:index>`,3.2.0,3.2.0,3.1.2
       :doc:`hipSPARSELt <hipsparselt:index>`,0.2.3,0.2.3,0.2.2
       :doc:`rocALUTION <rocalution:index>`,3.2.3,3.2.3,3.2.1
-      :doc:`rocBLAS <rocblas:index>`,4.4.1,4.4.0,4.3.0
+      :doc:`rocBLAS <rocblas:index>`,4.4.1,4.4.1,4.3.0
       :doc:`rocFFT <rocfft:index>`,1.0.32,1.0.32,1.0.31
       :doc:`rocRAND <rocrand:index>`,3.3.0,3.3.0,3.2.0
-      :doc:`rocSOLVER <rocsolver:index>`,3.28.2,3.28.0,3.27.0
+      :doc:`rocSOLVER <rocsolver:index>`,3.28.2,3.28.2,3.27.0
       :doc:`rocSPARSE <rocsparse:index>`,3.4.0,3.4.0,3.3.0
       :doc:`rocWMMA <rocwmma:index>`,1.7.0,1.7.0,1.6.0
       :doc:`Tensile <tensile:src/index>`,4.43.0,4.43.0,4.42.0
@@ -107,28 +107,28 @@ compatibility and system requirements.
       PRIMITIVES,.. _primitivelibs-support-compatibility-matrix:,,
       :doc:`hipCUB <hipcub:index>`,3.4.0,3.4.0,3.3.0
       :doc:`hipTensor <hiptensor:index>`,1.5.0,1.5.0,1.4.0
-      :doc:`rocPRIM <rocprim:index>`,3.4.1,3.4.0,3.3.0
+      :doc:`rocPRIM <rocprim:index>`,3.4.1,3.4.1,3.3.0
       :doc:`rocThrust <rocthrust:index>`,3.3.0,3.3.0,3.3.0
       ,,,
       SUPPORT LIBS,,,
       `hipother <https://github.com/ROCm/hipother>`_,6.4.43483,6.4.43483,6.3.42131
-      `rocm-core <https://github.com/ROCm/rocm-core>`_,6.4.2,6.4.1,6.3.0
+      `rocm-core <https://github.com/ROCm/rocm-core>`_,6.4.3,6.4.2,6.3.0
       `ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,N/A [#ROCT-rocr]_,N/A [#ROCT-rocr]_,N/A [#ROCT-rocr]_
       ,,,
       SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix:,,
-      :doc:`AMD SMI <amdsmi:index>`,25.5.1,25.4.2,24.7.1
+      :doc:`AMD SMI <amdsmi:index>`,25.5.1,25.5.1,24.7.1
       :doc:`ROCm Data Center Tool <rdc:index>`,0.3.0,0.3.0,0.3.0
       :doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0
-      :doc:`ROCm SMI <rocm_smi_lib:index>`,7.5.0,7.5.0,7.4.0
+      :doc:`ROCm SMI <rocm_smi_lib:index>`,7.7.0,7.5.0,7.4.0
       :doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,1.1.0,1.1.0,1.1.0
       ,,,
       PERFORMANCE TOOLS,,,
       :doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,1.4.0,1.4.0,1.4.0
-      :doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.1.1,3.1.0,3.0.0
-      :doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.0.2,1.0.1,0.1.0
-      :doc:`ROCProfiler <rocprofiler:index>`,2.0.60402,2.0.60401,2.0.60300
+      :doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.1.1,3.1.1,3.0.0
+      :doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.0.2,1.0.2,0.1.0
+      :doc:`ROCProfiler <rocprofiler:index>`,2.0.60403,2.0.60402,2.0.60300
       :doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,0.6.0,0.6.0,0.5.0
-      :doc:`ROCTracer <roctracer:index>`,4.1.60402,4.1.60401,4.1.60300
+      :doc:`ROCTracer <roctracer:index>`,4.1.60403,4.1.60402,4.1.60300
       ,,,
       DEVELOPMENT TOOLS,,,
       :doc:`HIPIFY <hipify:index>`,19.0.0,19.0.0,18.0.0.24455
@@ -141,16 +141,17 @@ compatibility and system requirements.
       COMPILERS,.. _compilers-support-compatibility-matrix:,,
       `clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A
       :doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1
-      `Flang <https://github.com/ROCm/flang>`_,19.0.0.25224,19.0.0.25184,18.0.0.24455
-      :doc:`llvm-project <llvm-project:index>`,19.0.0.25224,19.0.0.25184,18.0.0.24491
-      `OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,19.0.0.25224,19.0.0.25184,18.0.0.24491
+      `Flang <https://github.com/ROCm/flang>`_,19.0.0.25224,19.0.0.25224,18.0.0.24455
+      :doc:`llvm-project <llvm-project:index>`,19.0.0.25224,19.0.0.25224,18.0.0.24491
+      `OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,19.0.0.25224,19.0.0.25224,18.0.0.24491
       ,,,
       RUNTIMES,.. _runtime-support-compatibility-matrix:,,
-      :doc:`AMD CLR <hip:understand/amd_clr>`,6.4.43484,6.4.43483,6.3.42131
-      :doc:`HIP <hip:index>`,6.4.43484,6.4.43483,6.3.42131
+      :doc:`AMD CLR <hip:understand/amd_clr>`,6.4.43484,6.4.43484,6.3.42131
+      :doc:`HIP <hip:index>`,6.4.43484,6.4.43484,6.3.42131
       `OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0
       :doc:`ROCr Runtime <rocr-runtime:index>`,1.15.0,1.15.0,1.14.0
 
+
 .. rubric:: Footnotes
 
 .. [#mi300x] Oracle Linux and Azure Linux are supported only on AMD Instinct MI300X.
@@ -241,6 +242,10 @@ Expand for full historical view of:
    .. [#mi300_602-past-60] **For ROCm 6.0.2** - MI300A (gfx942) is supported on Ubuntu 22.04.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.3.
    .. [#mi300_600-past-60] **For ROCm 6.0.0** - MI300A (gfx942) is supported on Ubuntu 22.04.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.3.
    .. [#verl_compat] verl is only supported on ROCm 6.2.0.
+   .. [#stanford-megatron-lm_compat] Stanford Megatron-LM is only supported on ROCm 6.3.0.
+   .. [#dgl_compat] DGL is only supported on ROCm 6.4.0.
+   .. [#megablocks_compat] Megablocks is only supported on ROCm 6.3.0.
+   .. [#taichi_compat] Taichi is only supported on ROCm 6.3.2.
    .. [#kfd_support-past-60] As of ROCm 6.4.0, forward and backward compatibility between the AMD Kernel-mode GPU Driver (KMD) and its user space software is provided up to a year apart. For earlier ROCm releases, the compatibility is provided for +/- 2 releases. The tested user space versions on this page were accurate as of the time of initial ROCm release. For the most up-to-date information, see the latest version of this information at `User and kernel-space support matrix <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/user-kernel-space-compat-matrix.html>`_.
    .. [#ROCT-rocr-past-60] Starting from ROCm 6.3.0, the ROCT Thunk Interface is included as part of the ROCr runtime package.
    

docs/compatibility/ml-compatibility/dgl-compatibility.rst

@@ -42,16 +42,16 @@ GAT, GCN and GraphSage. Using these we can support a variety of use-cases such a
 - 1D (Temporal) and 2D (Image) Classification
 - Drug Discovery
 
-Refer to :doc:`ROCm DGL blog posts <https://rocm.blogs.amd.com/blog/tag/dgl.html>` 
-for examples and best practices to optimize your training workflows on AMD GPUs. 
+Multiple use cases of DGL have been tested and verified.
+However, a recommended example follows a drug discovery pipeline using the ``SE3Transformer``.
+Refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`_, 
+where you can search for DGL examples and best practices to optimize your training workflows on AMD GPUs. 
 
 Coverage includes:
 
 - Single-GPU training/inference
 - Multi-GPU training
 
-Benchmarking details are included in the :doc:`Benchmarks` section.
-
 
 .. _dgl-docker-compat:
 
@@ -252,4 +252,4 @@ Unsupported functions
 * ``gather_mm_idx_b``
 * ``pgexplainer``
 * ``sample_labors_prob``
-* ``sample_labors_noprob``
+* ``sample_labors_noprob``

docs/compatibility/ml-compatibility/jax-compatibility.rst

@@ -97,7 +97,7 @@ Docker image compatibility
 AMD validates and publishes ready-made `ROCm JAX Docker images <https://hub.docker.com/r/rocm/jax>`_
 with ROCm backends on Docker Hub. The following Docker image tags and
 associated inventories represent the latest JAX version from the official Docker Hub and are validated for
-`ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`_. Click the |docker-icon|
+`ROCm 6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`_. Click the |docker-icon|
 icon to view the image on Docker Hub.
 
 .. list-table:: JAX Docker image components
@@ -110,7 +110,7 @@ icon to view the image on Docker Hub.
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.1-jax0.4.35-py3.12/images/sha256-7a0745a2a2758bdf86397750bac00e9086cbf67d170cfdbb08af73f7c7d18a6a"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>
+           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.2-jax0.4.35-py3.12/images/sha256-8918fa806a172c1a10eb2f57131eb31b5d7c8fa1656b8729fe7d3d736112de83"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>
 
       - `0.4.35 <https://github.com/ROCm/jax/releases/tag/rocm-jax-v0.4.35>`_
       - Ubuntu 24.04
@@ -118,7 +118,7 @@ icon to view the image on Docker Hub.
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.1-jax0.4.35-py3.10/images/sha256-5f9e8d6e6e69fdc9a1a3f2ba3b1234c3f46c53b7468538c07fd18b00899da54f"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>
+           <a href="https://hub.docker.com/layers/rocm/jax/rocm6.4.2-jax0.4.35-py3.10/images/sha256-a394be13c67b7fc602216abee51233afd4b6cb7adaa57ca97e688fba82f9ad79"><i class="fab fa-docker fa-lg"></i> rocm/jax</a>
 
       - `0.4.35 <https://github.com/ROCm/jax/releases/tag/rocm-jax-v0.4.35>`_
       - Ubuntu 22.04

docs/compatibility/ml-compatibility/megablocks-compatibility.rst

@@ -0,0 +1,93 @@
+:orphan:
+
+.. meta::
+    :description: Megablocks compatibility
+    :keywords: GPU, megablocks, compatibility
+
+.. version-set:: rocm_version latest
+
+********************************************************************************
+Megablocks compatibility
+********************************************************************************
+
+Megablocks is a light-weight library for mixture-of-experts (MoE) training. 
+The core of the system is efficient "dropless-MoE" and standard MoE layers. 
+Megablocks is integrated with `https://github.com/stanford-futuredata/Megatron-LM <https://github.com/stanford-futuredata/Megatron-LM>`_, 
+where data and pipeline parallel training of MoEs is supported.
+
+* ROCm support for Megablocks is hosted in the official `https://github.com/ROCm/megablocks <https://github.com/ROCm/megablocks>`_ repository. 
+* Due to independent compatibility considerations, this location differs from the `https://github.com/stanford-futuredata/Megatron-LM <https://github.com/stanford-futuredata/Megatron-LM>`_ upstream repository. 
+* Use the prebuilt :ref:`Docker image <megablocks-docker-compat>` with ROCm, PyTorch, and Megablocks preinstalled. 
+* See the :doc:`ROCm Megablocks installation guide <rocm-install-on-linux:install/3rd-party/megablocks-install>` to install and get started.
+
+.. note::
+
+  Megablocks is supported on ROCm 6.3.0.
+
+Supported devices
+================================================================================
+
+- **Officially Supported**: AMD Instinct MI300X
+- **Partially Supported** (functionality or performance limitations): AMD Instinct MI250X, MI210X
+
+Supported models and features
+================================================================================
+
+This section summarizes the Megablocks features supported by ROCm.
+
+* Distributed Pre-training
+* Activation Checkpointing and Recomputation
+* Distributed Optimizer
+* Mixture-of-Experts
+* dropless-Mixture-of-Experts
+
+
+.. _megablocks-recommendations:
+
+Use cases and recommendations
+================================================================================
+
+The `ROCm Megablocks blog posts <https://rocm.blogs.amd.com/artificial-intelligence/megablocks/README.html>`_ 
+guide how to leverage the ROCm platform for pre-training using the Megablocks framework. 
+It features how to pre-process datasets and how to begin pre-training on AMD GPUs through:
+
+* Single-GPU pre-training
+* Multi-GPU pre-training
+
+
+.. _megablocks-docker-compat:
+
+Docker image compatibility
+================================================================================
+
+.. |docker-icon| raw:: html
+
+   <i class="fab fa-docker"></i>
+
+AMD validates and publishes `ROCm Megablocks images <https://hub.docker.com/r/rocm/megablocks/tags>`_
+with ROCm and Pytorch backends on Docker Hub. The following Docker image tags and associated
+inventories represent the latest Megatron-LM version from the official Docker Hub.
+The Docker images have been validated for `ROCm 6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_.
+Click |docker-icon| to view the image on Docker Hub.
+
+.. list-table:: 
+    :header-rows: 1
+    :class: docker-image-compatibility
+
+    * - Docker image
+      - ROCm
+      - Megablocks
+      - PyTorch
+      - Ubuntu
+      - Python
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/megablocks/megablocks-0.7.0_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-372ff89b96599019b8f5f9db469c84add2529b713456781fa62eb9a148659ab4"><i class="fab fa-docker fa-lg"></i> rocm/megablocks</a>
+      - `6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_
+      - `0.7.0 <https://github.com/databricks/megablocks/releases/tag/v0.7.0>`_
+      - `2.4.0 <https://github.com/ROCm/pytorch/tree/release/2.4>`_
+      - 24.04
+      - `3.12.9 <https://www.python.org/downloads/release/python-3129/>`_
+
+

docs/compatibility/ml-compatibility/pytorch-compatibility.rst

@@ -95,7 +95,7 @@ Docker image compatibility
 
 AMD validates and publishes `PyTorch images <https://hub.docker.com/r/rocm/pytorch>`__
 with ROCm backends on Docker Hub. The following Docker image tags and associated
-inventories were tested on `ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__.
+inventories were tested on `ROCm 6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`__.
 Click |docker-icon| to view the image on Docker Hub.
 
 .. list-table:: PyTorch Docker image components
@@ -112,127 +112,118 @@ Click |docker-icon| to view the image on Docker Hub.
       - MAGMA
       - UCX
       - OMPI
-      - OFED
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.6.0/images/sha256-c76af9bfb1c25b0f40d4c29e8652105c57250bf018d23ff595b06bd79666fdd7"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.6.0/images/sha256-6a287591500b4048a9556c1ecc92bc411fd3d552f6c8233bc399f18eb803e8d6"><i class="fab fa-docker fa-lg"></i></a>
 
       - `2.6.0 <https://github.com/ROCm/pytorch/tree/release/2.6>`__
       - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
       - `1.6.0 <https://github.com/ROCm/apex/tree/release/1.6.0>`__
       - `0.21.0 <https://github.com/pytorch/vision/tree/v0.21.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
       - `master <https://bitbucket.org/icl/magma/src/master/>`__
-      - `1.16.0 <https://github.com/openucx/ucx/tree/v1.16.0>`__
+      - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.16.0>`__
       - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.6.0/images/sha256-f9d226135d51831c810dcb1251636ec61f85c65fcdda03e188c053a5d4f6585b"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.10_pytorch_release_2.6.0/images/sha256-06b967629ba6657709f04169832cd769a11e6b491e8b1394c361d42d7a0c8b43"><i class="fab fa-docker fa-lg"></i></a>
 
       - `2.6.0 <https://github.com/ROCm/pytorch/tree/release/2.6>`__
       - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `3.10 <https://www.python.org/downloads/release/python-31017/>`__
       - `1.6.0 <https://github.com/ROCm/apex/tree/release/1.6.0>`__
       - `0.21.0 <https://github.com/pytorch/vision/tree/v0.21.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
       - `master <https://bitbucket.org/icl/magma/src/master/>`__
       - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
       - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.5.1/images/sha256-3490e74d4f43dcdb3351dd334108d1ccd47e5a687c0523a2424ac1bcdd3dd6dd"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.5.1/images/sha256-62022414217ef6de33ac5b1341e57db8a48e8573fa2ace12d48aa5edd4b99ef0"><i class="fab fa-docker fa-lg"></i></a>
 
       - `2.5.1 <https://github.com/ROCm/pytorch/tree/release/2.5>`__
       - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
       - `1.5.0 <https://github.com/ROCm/apex/tree/release/1.5.0>`__
       - `0.20.1 <https://github.com/pytorch/vision/tree/v0.20.1>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
       - `master <https://bitbucket.org/icl/magma/src/master/>`__
       - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.10.0>`__
       - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.5.1/images/sha256-26c5dfffb4a54625884abca83166940f17dd27bc75f1b24f6e80fbcb7d4e9afb"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.11_pytorch_release_2.5.1/images/sha256-469a7f74fc149aff31797e011ee41978f6a190adc69fa423b3c6a718a77bd985"><i class="fab fa-docker fa-lg"></i></a>
 
       - `2.5.1 <https://github.com/ROCm/pytorch/tree/release/2.5>`__
       - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `3.11 <https://www.python.org/downloads/release/python-31113/>`__
       - `1.5.0 <https://github.com/ROCm/apex/tree/release/1.5.0>`__
       - `0.20.1 <https://github.com/pytorch/vision/tree/v0.20.1>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
       - `master <https://bitbucket.org/icl/magma/src/master/>`__
       - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
       - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.4.1/images/sha256-f378a24561fa6efc178b6dc93fc7d82e5b93653ecd59c89d4476674d29e1284d"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.10_pytorch_release_2.5.1/images/sha256-37f41a1cd94019688669a1b20d33ea74156e0c129ef6b8270076ef214a6a1a2c"><i class="fab fa-docker fa-lg"></i></a>
+
+      - `2.5.1 <https://github.com/ROCm/pytorch/tree/release/2.5>`__
+      - 22.04
+      - `3.10 <https://www.python.org/downloads/release/python-31017/>`__
+      - `1.5.0 <https://github.com/ROCm/apex/tree/release/1.5.0>`__
+      - `0.20.1 <https://github.com/pytorch/vision/tree/v0.20.1>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
+      - `master <https://bitbucket.org/icl/magma/src/master/>`__
+      - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
+      - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.4.1/images/sha256-60824ba83dc1b9d94164925af1f81c0235c105dd555091ec04c57e05177ead1b"><i class="fab fa-docker fa-lg"></i></a>
 
       - `2.4.1 <https://github.com/ROCm/pytorch/tree/release/2.4>`__
       - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
       - `1.4.0 <https://github.com/ROCm/apex/tree/release/1.4.0>`__
       - `0.19.0 <https://github.com/pytorch/vision/tree/v0.19.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
       - `master <https://bitbucket.org/icl/magma/src/master/>`__
       - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.16.0>`__
       - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.4.1/images/sha256-2308dbd0e650b7bf8d548575cbb6e2bdc021f9386384ce570da16d58ee684d22"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu22.04_py3.10_pytorch_release_2.4.1/images/sha256-fe944fe083312f901be6891ab4d3ffebf2eaf2cf4f5f0f435ef0b76ec714fabd"><i class="fab fa-docker fa-lg"></i></a>
 
       - `2.4.1 <https://github.com/ROCm/pytorch/tree/release/2.4>`__
       - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `3.10 <https://www.python.org/downloads/release/python-31017/>`__
       - `1.4.0 <https://github.com/ROCm/apex/tree/release/1.4.0>`__
       - `0.19.0 <https://github.com/pytorch/vision/tree/v0.19.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13.0>`__
+      - `2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
       - `master <https://bitbucket.org/icl/magma/src/master/>`__
       - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
       - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu24.04_py3.12_pytorch_release_2.3.0/images/sha256-eefd2ab019728f91f94c5e6a9463cb0ea900b3011458d18fe5d88e50c0b57d86"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.2_ubuntu24.04_py3.12_pytorch_release_2.3.0/images/sha256-1d59251c47170c5b8960d1172a4dbe52f5793d8966edd778f168eaf32d56661a"><i class="fab fa-docker fa-lg"></i></a>
 
       - `2.3.0 <https://github.com/ROCm/pytorch/tree/release/2.3>`__
       - 24.04
-      - `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `3.12 <https://www.python.org/downloads/release/python-31210/>`__
       - `1.3.0 <https://github.com/ROCm/apex/tree/release/1.3.0>`__
       - `0.18.0 <https://github.com/pytorch/vision/tree/v0.18.0>`__
       - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13>`__
       - `master <https://bitbucket.org/icl/magma/src/master/>`__
       - `1.16.0+ds-5ubuntu1 <https://github.com/openucx/ucx/tree/v1.16.0>`__
       - `4.1.6-7ubuntu2 <https://github.com/open-mpi/ompi/tree/v4.1.6>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/pytorch/rocm6.4.1_ubuntu22.04_py3.10_pytorch_release_2.3.0/images/sha256-473643226ab0e93a04720b256ed772619878abf9c42b9f84828cefed522696fd"><i class="fab fa-docker fa-lg"></i></a>
-
-      - `2.3.0 <https://github.com/ROCm/pytorch/tree/release/2.3>`__
-      - 22.04
-      - `3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `1.3.0 <https://github.com/ROCm/apex/tree/release/1.3.0>`__
-      - `0.18.0 <https://github.com/pytorch/vision/tree/v0.18.0>`__
-      - `2.13.0 <https://github.com/tensorflow/tensorboard/tree/2.13>`__
-      - `master <https://bitbucket.org/icl/magma/src/master/>`__
-      - `1.12.1~rc2-1 <https://github.com/openucx/ucx/tree/v1.12.1>`__
-      - `4.1.2-2ubuntu1 <https://github.com/open-mpi/ompi/tree/v4.1.2>`__
-      - `5.3-1.0.5.0 <https://content.mellanox.com/ofed/MLNX_OFED-5.3-1.0.5.0/MLNX_OFED_LINUX-5.3-1.0.5.0-ubuntu20.04-x86_64.tgz>`__
 
 Key ROCm libraries for PyTorch
 ================================================================================

docs/compatibility/ml-compatibility/taichi-compatibility.rst

@@ -0,0 +1,76 @@
+:orphan:
+
+.. meta::
+    :description: Taichi compatibility
+    :keywords: GPU, Taichi compatibility
+
+.. version-set:: rocm_version latest
+
+*******************************************************************************
+Taichi compatibility
+*******************************************************************************
+
+`Taichi <https://www.taichi-lang.org/>`_ is an open-source, imperative, and parallel 
+programming language designed for high-performance numerical computation. 
+Embedded in Python, it leverages just-in-time (JIT) compilation frameworks such as LLVM to accelerate 
+compute-intensive Python code by compiling it to native GPU or CPU instructions.
+
+Taichi is widely used across various domains, including real-time physical simulation, 
+numerical computing, augmented reality, artificial intelligence, computer vision, robotics, 
+visual effects in film and gaming, and general-purpose computing.
+
+* ROCm support for Taichi is hosted in the official `https://github.com/ROCm/taichi <https://github.com/ROCm/taichi>`_ repository.
+* Due to independent compatibility considerations, this location differs from the `https://github.com/taichi-dev <https://github.com/taichi-dev>`_ upstream repository.
+* Use the prebuilt :ref:`Docker image <taichi-docker-compat>` with ROCm, PyTorch, and Taichi preinstalled.
+* See the :doc:`ROCm Taichi installation guide <rocm-install-on-linux:install/3rd-party/taichi-install>` to install and get started.
+
+.. note::
+
+	Taichi is supported on ROCm 6.3.2.
+
+Supported devices and features
+===============================================================================
+There is support through the ROCm software stack for all Taichi GPU features on AMD Instinct MI250X and MI210X series GPUs with the exception of Taichi’s GPU rendering system, CGUI.
+AMD Instinct MI300X series GPUs will be supported by November.
+
+.. _taichi-recommendations:
+
+Use cases and recommendations
+================================================================================
+To fully leverage Taichi's performance capabilities in compute-intensive tasks, it is best to adhere to specific coding patterns and utilize Taichi decorators. 
+A collection of example use cases is available in the `https://github.com/ROCm/taichi_examples <https://github.com/ROCm/taichi_examples>`_ repository, 
+providing practical insights and foundational knowledge for working with the Taichi programming language. 
+You can also refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`_ to search for Taichi examples and best practices to optimize your workflows on AMD GPUs.
+
+.. _taichi-docker-compat:
+
+Docker image compatibility
+================================================================================
+
+.. |docker-icon| raw:: html
+
+   <i class="fab fa-docker"></i>
+
+AMD validates and publishes ready-made `ROCm Taichi Docker images <https://hub.docker.com/r/rocm/taichi/tags>`_
+with ROCm backends on Docker Hub. The following Docker image tags and associated inventories 
+represent the latest Taichi version from the official Docker Hub.
+The Docker images have been validated for `ROCm 6.3.2 <https://rocm.docs.amd.com/en/docs-6.3.2/about/release-notes.html>`_. 
+Click |docker-icon| to view the image on Docker Hub.
+
+.. list-table:: 
+    :header-rows: 1
+    :class: docker-image-compatibility
+
+    * - Docker image
+      - ROCm
+      - Taichi
+      - Ubuntu
+      - Python
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/taichi/taichi-1.8.0b1_rocm6.3.2_ubuntu22.04_py3.10.12/images/sha256-e016964a751e6a92199032d23e70fa3a564fff8555afe85cd718f8aa63f11fc6"><i class="fab fa-docker fa-lg"></i> rocm/taichi</a>
+      - `6.3.2 <https://repo.radeon.com/rocm/apt/6.3.2/>`_
+      - `1.8.0b1 <https://github.com/taichi-dev/taichi>`_
+      - 22.04
+      - `3.10.12 <https://www.python.org/downloads/release/python-31012/>`_

docs/compatibility/ml-compatibility/tensorflow-compatibility.rst

@@ -56,7 +56,7 @@ Docker image compatibility
 AMD validates and publishes ready-made `TensorFlow images
 <https://hub.docker.com/r/rocm/tensorflow>`__ with ROCm backends on
 Docker Hub. The following Docker image tags and associated inventories are
-validated for `ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__. Click
+validated for `ROCm 6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`__. Click
 the |docker-icon| icon to view the image on Docker Hub.
 
 .. list-table:: TensorFlow Docker image components
@@ -65,128 +65,61 @@ the |docker-icon| icon to view the image on Docker Hub.
     * - Docker image
       - TensorFlow
       - Ubuntu
-      - Dev
       - Python
       - TensorBoard
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4-py3.12-tf2.18-dev/images/sha256-fa9cf5fa6c6079a7118727531ccd0056c6e3224a42c3d6e78a49e7781daafff4"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.12-tf2.18-dev/images/sha256-96754ce2d30f729e19b497279915b5212ba33d5e408e7e5dd3f2304d87e3441e"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
 
-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
       - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `Python 3.12 <https://www.python.org/downloads/release/python-31210/>`__
       - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.18-runtime/images/sha256-d14d8c4989e7c9a60f4e72461b9e349de72347c6162dcd6897e6f4f80ffbb440"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.10-tf2.18-dev/images/sha256-fa741508d383858e86985a9efac85174529127408102558ae2e3a4ac894eea1e"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
 
-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.18.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
+      - 22.04
+      - `Python 3.10 <https://www.python.org/downloads/release/python-31017/>`__
       - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.18-dev/images/sha256-081e5bd6615a5dc17247ebd2ccc26895c3feeff086720400fa39b477e60a77c0"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.12-tf2.17-dev/images/sha256-3a0aef09f2a8833c2b64b85874dd9449ffc2ad257351857338ff5b706c03a418"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
 
-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
-      - dev
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.18-runtime/images/sha256-bf369637378264f4af6ddad5ca8b8611d3e372ffbea9ab7a06f1e122f0a0867b"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.18.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.18.0 <https://github.com/tensorflow/tensorboard/tree/2.18.0>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.17-dev/images/sha256-5a502008c50d0b6508e6027f911bdff070a7493700ae064bed74e1d22b91ed50"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
       - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `Python 3.12 <https://www.python.org/downloads/release/python-31210/>`__
       - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.17-runtime/images/sha256-1ee5dfffceb71ac66617ada33de3a10de0cb74199cc4b82441192e5e92fa2ddf"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.10-tf2.17-dev/images/sha256-bc7341a41ebe7ab261aa100732874507c452421ef733e408ac4f05ed453b0bc5"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
 
-      - `tensorflow-rocm 2.18.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-3124/>`__
-      - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.17-dev/images/sha256-109218ad92bfae83bbd2710475f7502166e1ed54ca0b9748a9cbc3f5a1d75af1"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.17.1-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.17.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
       - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `Python 3.10 <https://www.python.org/downloads/release/python-31017/>`__
       - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.17-runtime/images/sha256-5d78bd5918d394f92263daa2990e88d695d27200dd90ed83ec64d20c7661c9c1"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.12-tf2.16-dev/images/sha256-4841a8df7c340dab79bf9362dad687797649a00d594e0832eb83ea6880a40d3b"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
 
-      - `tensorflow-rocm 2.17.1 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.17.1-cp310-cp310-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.17.1 <https://github.com/tensorflow/tensorboard/tree/2.17.1>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.16-dev/images/sha256-b09b1ad921c09c687b7c916141051e9fcf15539a5686e5aa67c689195a522719"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - dev
+      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
       - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
+      - `Python 3.12 <https://www.python.org/downloads/release/python-31210/>`__
       - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__
 
     * - .. raw:: html
 
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.12-tf2.16-runtime/images/sha256-20dbd824e85558abfe33fc9283cc547d88cde3c623fe95322743a5082f883a64"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
+           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.2-py3.10-tf2.16-dev/images/sha256-883fa95aba960c58a3e46fceaa18f03ede2c7df89b8e9fd603ab2d47e0852897"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
 
-      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 24.04
-      - `Python 3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
-      - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.16-dev/images/sha256-36c4fa047c86e2470ac473ec1429aea6d4b8934b90ffeb34d1afab40e7e5b377"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.16.2 <https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.16-dev/images/sha256-36c4fa047c86e2470ac473ec1429aea6d4b8934b90ffeb34d1afab40e7e5b377>`__
-      - dev
+      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.2/tensorflow_rocm-2.16.2-cp310-cp310-manylinux_2_28_x86_64.whl>`__
       - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
-      - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__
-
-    * - .. raw:: html
-
-           <a href="https://hub.docker.com/layers/rocm/tensorflow/rocm6.4.1-py3.10-tf2.16-runtime/images/sha256-a94150ffb81365234ebfa34e764db5474bc6ab7d141b56495eac349778dafcf3"><i class="fab fa-docker fa-lg"></i> rocm/tensorflow</a>
-
-      - `tensorflow-rocm 2.16.2 <https://repo.radeon.com/rocm/manylinux/rocm-rel-6.4.1/tensorflow_rocm-2.16.2-cp312-cp312-manylinux_2_28_x86_64.whl>`__
-      - runtime
-      - 22.04
-      - `Python 3.10.17 <https://www.python.org/downloads/release/python-31017/>`__
+      - `Python 3.10 <https://www.python.org/downloads/release/python-31017/>`__
       - `TensorBoard 2.16.2 <https://github.com/tensorflow/tensorboard/tree/2.16.2>`__
 
 

docs/compatibility/ml-compatibility/verl-compatibility.rst

@@ -16,56 +16,25 @@ verl offers a scalable, open-source fine-tuning solution optimized for AMD Insti
 * See the `verl documentation <https://verl.readthedocs.io/en/latest/>`_ for more information about verl. 
 * The official verl GitHub repository is `https://github.com/volcengine/verl <https://github.com/volcengine/verl>`_.
 * Use the AMD-validated :ref:`Docker images <verl-docker-compat>` with ROCm and verl preinstalled. 
-* See the :doc:`ROCm verl installation guide <rocm-install-on-linux:install/3rd-party/verl-install>` to get started.
+* See the :doc:`ROCm verl installation guide <rocm-install-on-linux:install/3rd-party/verl-install>` to install and get started.
 
 .. note::
 
 	verl is supported on ROCm 6.2.0.
 
-
 .. _verl-recommendations:
 
 Use cases and recommendations
 ================================================================================
 
-The benefits of verl in large-scale reinforcement leaning from human feedback (RLHF) are discussed in the `Reinforcement Learning from Human Feedback on AMD GPUs with verl and ROCm Integration <https://rocm.blogs.amd.com/artificial-intelligence/verl-large-scale/README.html>`_ blog.
-
-.. _verl-docker-compat:
-
-Docker image compatibility
-================================================================================
-
-.. |docker-icon| raw:: html
-
-   <i class="fab fa-docker"></i>
-
-AMD validates and publishes ready-made `ROCm verl Docker images <https://hub.docker.com/r/rocm/verl>`_
-with ROCm backends on Docker Hub. The following Docker image tags and associated inventories represent the latest verl version from the official Docker Hub. The Docker images have been validated for `ROCm 6.2.0 <https://repo.radeon.com/rocm/apt/6.2/>`_. 
-
-.. list-table:: 
-    :header-rows: 1
-
-    *   - Docker image
-        - verl
-        - Linux
-        - Pytorch
-        - Python
-        - vllm
-
-    *   - .. raw:: html
-
-            <a href="https://hub.docker.com/layers/rocm/verl/verl-0.3.0.post0_rocm6.2_vllm0.6.3/images/sha256-cbe423803fd7850448b22444176bee06f4dcf22cd3c94c27732752d3a39b04b2"><i class="fab fa-docker fa-lg"></i> rocm/verl</a>
-        - `0.3.0post0 <https://github.com/volcengine/verl/releases/tag/v0.3.0.post0>`_
-        - Ubuntu 20.04
-        - `2.5.0 <https://download.pytorch.org/whl/cu118/torch-2.5.0%2Bcu118-cp39-cp39-linux_x86_64.whl#sha256=1ee24b267418c37b297529ede875b961e382c1c365482f4142af2398b92ed127>`_
-        - `3.9.19 <https://www.python.org/downloads/release/python-3919/>`_
-        - `0.6.4 <https://github.com/vllm-project/vllm/releases/tag/v0.6.4>`_
+The benefits of verl in large-scale reinforcement learning from human feedback (RLHF) are discussed in the `Reinforcement Learning from Human Feedback on AMD GPUs with verl and ROCm Integration <https://rocm.blogs.amd.com/artificial-intelligence/verl-large-scale/README.html>`_ blog.
 
+.. _verl-supported_features:
 
 Supported features
 ===============================================================================
 
-The following table shows verl and ROCm support for GPU-accelerated modules.
+The following table shows verl on ROCm support for GPU-accelerated modules.
 
 .. list-table::
     :header-rows: 1
@@ -77,9 +46,41 @@ The following table shows verl and ROCm support for GPU-accelerated modules.
     * - ``FSDP``
       - Training engine
       - 0.3.0.post0
-      - 6.2
+      - 6.2.0
     * - ``vllm``
       - Inference engine
       - 0.3.0.post0
-      - 6.2
-  
+      - 6.2.0
+
+.. _verl-docker-compat:
+
+Docker image compatibility
+================================================================================
+
+.. |docker-icon| raw:: html
+
+   <i class="fab fa-docker"></i>
+
+AMD validates and publishes ready-made `ROCm verl Docker images <https://hub.docker.com/r/rocm/verl/tags>`_
+with ROCm backends on Docker Hub. The following Docker image tags and associated inventories represent the available verl versions from the official Docker Hub. 
+
+.. list-table:: 
+    :header-rows: 1
+
+    *   - Docker image
+        - ROCm
+        - verl
+        - Ubuntu
+        - Pytorch
+        - Python
+        - vllm
+
+    *   - .. raw:: html
+
+            <a href="https://hub.docker.com/layers/rocm/verl/verl-0.3.0.post0_rocm6.2_vllm0.6.3/images/sha256-cbe423803fd7850448b22444176bee06f4dcf22cd3c94c27732752d3a39b04b2"><i class="fab fa-docker fa-lg"></i> rocm/verl</a>
+        - `6.2.0 <https://repo.radeon.com/rocm/apt/6.2/>`_
+        - `0.3.0post0 <https://github.com/volcengine/verl/releases/tag/v0.3.0.post0>`_
+        - 20.04
+        - `2.5.0 <https://github.com/ROCm/pytorch/tree/release/2.5>`_
+        - `3.9.19 <https://www.python.org/downloads/release/python-3919/>`_
+        - `0.6.3 <https://github.com/vllm-project/vllm/releases/tag/v0.6.3>`_

docs/conf.py

@@ -82,20 +82,25 @@ project = "ROCm Documentation"
 project_path = os.path.abspath(".").replace("\\", "/")
 author = "Advanced Micro Devices, Inc."
 copyright = "Copyright (c) 2025 Advanced Micro Devices, Inc. All rights reserved."
-version = "6.4.2"
-release = "6.4.2"
+version = "6.4.3"
+release = "6.4.3"
 setting_all_article_info = True
 all_article_info_os = ["linux", "windows"]
 all_article_info_author = ""
 
 # pages with specific settings
 article_pages = [
-    {"file": "about/release-notes", "os": ["linux"], "date": "2025-07-21"},
+    {"file": "about/release-notes", "os": ["linux"], "date": "2025-08-07"},
     {"file": "release/changelog", "os": ["linux"],},
     {"file": "compatibility/compatibility-matrix", "os": ["linux"]},
     {"file": "compatibility/ml-compatibility/pytorch-compatibility", "os": ["linux"]},
     {"file": "compatibility/ml-compatibility/tensorflow-compatibility", "os": ["linux"]},
     {"file": "compatibility/ml-compatibility/jax-compatibility", "os": ["linux"]},
+    {"file": "compatibility/ml-compatibility/verl-compatibility", "os": ["linux"]},
+    {"file": "compatibility/ml-compatibility/stanford-megatron-lm-compatibility", "os": ["linux"]},
+    {"file": "compatibility/ml-compatibility/dgl-compatibility", "os": ["linux"]},
+    {"file": "compatibility/ml-compatibility/megablocks-compatibility", "os": ["linux"]},
+    {"file": "compatibility/ml-compatibility/taichi-compatibility", "os": ["linux"]},
     {"file": "how-to/deep-learning-rocm", "os": ["linux"]},
 
     {"file": "how-to/rocm-for-ai/index", "os": ["linux"]},
@@ -142,6 +147,8 @@ article_pages = [
     {"file": "how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-0.8.5-20250521", "os": ["linux"]},
     {"file": "how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-0.9.0.1-20250605", "os": ["linux"]},
     {"file": "how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-0.9.0.1-20250702", "os": ["linux"]},
+    {"file": "how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-0.9.1-20250702", "os": ["linux"]},
+    {"file": "how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-0.9.1-20250715", "os": ["linux"]},
     {"file": "how-to/rocm-for-ai/inference/benchmark-docker/pytorch-inference", "os": ["linux"]},
     {"file": "how-to/rocm-for-ai/inference/deploy-your-model", "os": ["linux"]},
 

docs/data/how-to/rocm-for-ai/inference/previous-versions/vllm_0.9.1_20250715-benchmark_models.yaml

@@ -0,0 +1,163 @@
+vllm_benchmark:
+  unified_docker:
+    latest:
+      # TODO: update me
+      pull_tag: rocm/vllm:rocm6.4.1_vllm_0.9.1_20250715
+      docker_hub_url: https://hub.docker.com/layers/rocm/vllm/rocm6.4.1_vllm_0.9.1_20250715/images/sha256-4a429705fa95a58f6d20aceab43b1b76fa769d57f32d5d28bd3f4e030e2a78ea
+      rocm_version: 6.4.1
+      vllm_version: 0.9.1 (0.9.2.dev364+gb432b7a28.rocm641)
+      pytorch_version: 2.7.0+gitf717b2a
+      hipblaslt_version: 0.15
+  model_groups:
+    - group: Meta Llama
+      tag: llama
+      models:
+      - model: Llama 3.1 8B
+        mad_tag: pyt_vllm_llama-3.1-8b
+        model_repo: meta-llama/Llama-3.1-8B-Instruct
+        url: https://huggingface.co/meta-llama/Llama-3.1-8B
+        precision: float16
+      - model: Llama 3.1 70B
+        mad_tag: pyt_vllm_llama-3.1-70b
+        model_repo: meta-llama/Llama-3.1-70B-Instruct
+        url: https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct
+        precision: float16
+      - model: Llama 3.1 405B
+        mad_tag: pyt_vllm_llama-3.1-405b
+        model_repo: meta-llama/Llama-3.1-405B-Instruct
+        url: https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct
+        precision: float16
+      - model: Llama 2 7B
+        mad_tag: pyt_vllm_llama-2-7b
+        model_repo: meta-llama/Llama-2-7b-chat-hf
+        url: https://huggingface.co/meta-llama/Llama-2-7b-chat-hf
+        precision: float16
+      - model: Llama 2 70B
+        mad_tag: pyt_vllm_llama-2-70b
+        model_repo: meta-llama/Llama-2-70b-chat-hf
+        url: https://huggingface.co/meta-llama/Llama-2-70b-chat-hf
+        precision: float16
+      - model: Llama 3.1 8B FP8
+        mad_tag: pyt_vllm_llama-3.1-8b_fp8
+        model_repo: amd/Llama-3.1-8B-Instruct-FP8-KV
+        url: https://huggingface.co/amd/Llama-3.1-8B-Instruct-FP8-KV
+        precision: float8
+      - model: Llama 3.1 70B FP8
+        mad_tag: pyt_vllm_llama-3.1-70b_fp8
+        model_repo: amd/Llama-3.1-70B-Instruct-FP8-KV
+        url: https://huggingface.co/amd/Llama-3.1-70B-Instruct-FP8-KV
+        precision: float8
+      - model: Llama 3.1 405B FP8
+        mad_tag: pyt_vllm_llama-3.1-405b_fp8
+        model_repo: amd/Llama-3.1-405B-Instruct-FP8-KV
+        url: https://huggingface.co/amd/Llama-3.1-405B-Instruct-FP8-KV
+        precision: float8
+    - group: Mistral AI
+      tag: mistral
+      models:
+      - model: Mixtral MoE 8x7B
+        mad_tag: pyt_vllm_mixtral-8x7b
+        model_repo: mistralai/Mixtral-8x7B-Instruct-v0.1
+        url: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
+        precision: float16
+      - model: Mixtral MoE 8x22B
+        mad_tag: pyt_vllm_mixtral-8x22b
+        model_repo: mistralai/Mixtral-8x22B-Instruct-v0.1
+        url: https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1
+        precision: float16
+      - model: Mistral 7B
+        mad_tag: pyt_vllm_mistral-7b
+        model_repo: mistralai/Mistral-7B-Instruct-v0.3
+        url: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3
+        precision: float16
+      - model: Mixtral MoE 8x7B FP8
+        mad_tag: pyt_vllm_mixtral-8x7b_fp8
+        model_repo: amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV
+        url: https://huggingface.co/amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV
+        precision: float8
+      - model: Mixtral MoE 8x22B FP8
+        mad_tag: pyt_vllm_mixtral-8x22b_fp8
+        model_repo: amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
+        url: https://huggingface.co/amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
+        precision: float8
+      - model: Mistral 7B FP8
+        mad_tag: pyt_vllm_mistral-7b_fp8
+        model_repo: amd/Mistral-7B-v0.1-FP8-KV
+        url: https://huggingface.co/amd/Mistral-7B-v0.1-FP8-KV
+        precision: float8
+    - group: Qwen
+      tag: qwen
+      models:
+      - model: Qwen2 7B
+        mad_tag: pyt_vllm_qwen2-7b
+        model_repo: Qwen/Qwen2-7B-Instruct
+        url: https://huggingface.co/Qwen/Qwen2-7B-Instruct
+        precision: float16
+      - model: Qwen2 72B
+        mad_tag: pyt_vllm_qwen2-72b
+        model_repo: Qwen/Qwen2-72B-Instruct
+        url: https://huggingface.co/Qwen/Qwen2-72B-Instruct
+        precision: float16
+      - model: QwQ-32B
+        mad_tag: pyt_vllm_qwq-32b
+        model_repo: Qwen/QwQ-32B
+        url: https://huggingface.co/Qwen/QwQ-32B
+        precision: float16
+        tunableop: true
+    - group: Databricks DBRX
+      tag: dbrx
+      models:
+      - model: DBRX Instruct
+        mad_tag: pyt_vllm_dbrx-instruct
+        model_repo: databricks/dbrx-instruct
+        url: https://huggingface.co/databricks/dbrx-instruct
+        precision: float16
+      - model: DBRX Instruct FP8
+        mad_tag: pyt_vllm_dbrx_fp8
+        model_repo: amd/dbrx-instruct-FP8-KV
+        url: https://huggingface.co/amd/dbrx-instruct-FP8-KV
+        precision: float8
+    - group: Google Gemma
+      tag: gemma
+      models:
+      - model: Gemma 2 27B
+        mad_tag: pyt_vllm_gemma-2-27b
+        model_repo: google/gemma-2-27b
+        url: https://huggingface.co/google/gemma-2-27b
+        precision: float16
+    - group: Cohere
+      tag: cohere
+      models:
+      - model: C4AI Command R+ 08-2024
+        mad_tag: pyt_vllm_c4ai-command-r-plus-08-2024
+        model_repo: CohereForAI/c4ai-command-r-plus-08-2024
+        url: https://huggingface.co/CohereForAI/c4ai-command-r-plus-08-2024
+        precision: float16
+      - model: C4AI Command R+ 08-2024 FP8
+        mad_tag: pyt_vllm_command-r-plus_fp8
+        model_repo: amd/c4ai-command-r-plus-FP8-KV
+        url: https://huggingface.co/amd/c4ai-command-r-plus-FP8-KV
+        precision: float8
+    - group: DeepSeek
+      tag: deepseek
+      models:
+      - model: DeepSeek MoE 16B
+        mad_tag: pyt_vllm_deepseek-moe-16b-chat
+        model_repo: deepseek-ai/deepseek-moe-16b-chat
+        url: https://huggingface.co/deepseek-ai/deepseek-moe-16b-chat
+        precision: float16
+    - group: Microsoft Phi
+      tag: phi
+      models:
+      - model: Phi-4
+        mad_tag: pyt_vllm_phi-4
+        model_repo: microsoft/phi-4
+        url: https://huggingface.co/microsoft/phi-4
+    - group: TII Falcon
+      tag: falcon
+      models:
+      - model: Falcon 180B
+        mad_tag: pyt_vllm_falcon-180b
+        model_repo: tiiuae/falcon-180B
+        url: https://huggingface.co/tiiuae/falcon-180B
+        precision: float16

docs/data/how-to/rocm-for-ai/inference/pytorch-inference-benchmark-models.yaml

@@ -1,6 +1,6 @@
 pytorch_inference_benchmark:
   unified_docker:
-    latest: &rocm-pytorch-docker-latest
+    latest:
       pull_tag: rocm/pytorch:latest
       docker_hub_url:
       rocm_version:
@@ -39,3 +39,19 @@ pytorch_inference_benchmark:
         model_repo: Wan-AI/Wan2.1-T2V-14B
         url: https://huggingface.co/Wan-AI/Wan2.1-T2V-14B
         precision: bfloat16
+    - group: Janus Pro
+      tag: janus-pro
+      models:
+      - model: Janus Pro 7B
+        mad_tag: pyt_janus_pro_inference
+        model_repo: deepseek-ai/Janus-Pro-7B
+        url: https://huggingface.co/deepseek-ai/Janus-Pro-7B
+        precision: bfloat16
+    - group: Hunyuan Video
+      tag: hunyuan
+      models:
+      - model: Hunyuan Video
+        mad_tag: pyt_hy_video
+        model_repo: tencent/HunyuanVideo
+        url: https://huggingface.co/tencent/HunyuanVideo
+        precision: float16

docs/data/how-to/rocm-for-ai/inference/sglang-benchmark-models.yaml

@@ -0,0 +1,17 @@
+sglang_benchmark:
+  unified_docker:
+    latest:
+      pull_tag: lmsysorg/sglang:v0.4.5-rocm630
+      docker_hub_url: https://hub.docker.com/layers/lmsysorg/sglang/v0.4.5-rocm630/images/sha256-63d2cb760a237125daf6612464cfe2f395c0784e21e8b0ea37d551cd10d3c951
+      rocm_version: 6.3.0
+      sglang_version: 0.4.5 (0.4.5-rocm)
+      pytorch_version: 2.6.0a0+git8d4926e
+  model_groups:
+    - group: DeepSeek
+      tag: deepseek
+      models:
+      - model: DeepSeek-R1-Distill-Qwen-32B
+        mad_tag: pyt_sglang_deepseek-r1-distill-qwen-32b
+        model_repo: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
+        url: https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
+        precision: bfloat16

docs/data/how-to/rocm-for-ai/inference/vllm-benchmark-models.yaml

@@ -2,11 +2,11 @@ vllm_benchmark:
   unified_docker:
     latest:
       # TODO: update me
-      pull_tag: rocm/vllm:rocm6.4.1_vllm_0.9.1_20250715
-      docker_hub_url: https://hub.docker.com/layers/rocm/vllm/rocm6.4.1_vllm_0.9.1_20250715/images/sha256-4a429705fa95a58f6d20aceab43b1b76fa769d57f32d5d28bd3f4e030e2a78ea
+      pull_tag: rocm/vllm:rocm6.4.1_vllm_0.10.0_20250812
+      docker_hub_url: https://hub.docker.com/layers/rocm/vllm/rocm6.4.1_vllm_0.10.0_20250812/images/sha256-4c277ad39af3a8c9feac9b30bf78d439c74d9b4728e788a419d3f1d0c30cacaa
       rocm_version: 6.4.1
-      vllm_version: 0.9.1 (0.9.2.dev364+gb432b7a28.rocm641)
-      pytorch_version: 2.7.0+gitf717b2a
+      vllm_version: 0.10.0 (0.10.1.dev395+g340ea86df.rocm641)
+      pytorch_version: 2.7.0+gitf717b2a (2.7.0+gitf717b2a)
       hipblaslt_version: 0.15
   model_groups:
     - group: Meta Llama
@@ -27,11 +27,6 @@ vllm_benchmark:
         model_repo: meta-llama/Llama-3.1-405B-Instruct
         url: https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct
         precision: float16
-      - model: Llama 2 7B
-        mad_tag: pyt_vllm_llama-2-7b
-        model_repo: meta-llama/Llama-2-7b-chat-hf
-        url: https://huggingface.co/meta-llama/Llama-2-7b-chat-hf
-        precision: float16
       - model: Llama 2 70B
         mad_tag: pyt_vllm_llama-2-70b
         model_repo: meta-llama/Llama-2-70b-chat-hf
@@ -65,11 +60,6 @@ vllm_benchmark:
         model_repo: mistralai/Mixtral-8x22B-Instruct-v0.1
         url: https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1
         precision: float16
-      - model: Mistral 7B
-        mad_tag: pyt_vllm_mistral-7b
-        model_repo: mistralai/Mistral-7B-Instruct-v0.3
-        url: https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3
-        precision: float16
       - model: Mixtral MoE 8x7B FP8
         mad_tag: pyt_vllm_mixtral-8x7b_fp8
         model_repo: amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV
@@ -80,72 +70,15 @@ vllm_benchmark:
         model_repo: amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
         url: https://huggingface.co/amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
         precision: float8
-      - model: Mistral 7B FP8
-        mad_tag: pyt_vllm_mistral-7b_fp8
-        model_repo: amd/Mistral-7B-v0.1-FP8-KV
-        url: https://huggingface.co/amd/Mistral-7B-v0.1-FP8-KV
-        precision: float8
     - group: Qwen
       tag: qwen
       models:
-      - model: Qwen2 7B
-        mad_tag: pyt_vllm_qwen2-7b
-        model_repo: Qwen/Qwen2-7B-Instruct
-        url: https://huggingface.co/Qwen/Qwen2-7B-Instruct
-        precision: float16
-      - model: Qwen2 72B
-        mad_tag: pyt_vllm_qwen2-72b
-        model_repo: Qwen/Qwen2-72B-Instruct
-        url: https://huggingface.co/Qwen/Qwen2-72B-Instruct
-        precision: float16
       - model: QwQ-32B
         mad_tag: pyt_vllm_qwq-32b
         model_repo: Qwen/QwQ-32B
         url: https://huggingface.co/Qwen/QwQ-32B
         precision: float16
         tunableop: true
-    - group: Databricks DBRX
-      tag: dbrx
-      models:
-      - model: DBRX Instruct
-        mad_tag: pyt_vllm_dbrx-instruct
-        model_repo: databricks/dbrx-instruct
-        url: https://huggingface.co/databricks/dbrx-instruct
-        precision: float16
-      - model: DBRX Instruct FP8
-        mad_tag: pyt_vllm_dbrx_fp8
-        model_repo: amd/dbrx-instruct-FP8-KV
-        url: https://huggingface.co/amd/dbrx-instruct-FP8-KV
-        precision: float8
-    - group: Google Gemma
-      tag: gemma
-      models:
-      - model: Gemma 2 27B
-        mad_tag: pyt_vllm_gemma-2-27b
-        model_repo: google/gemma-2-27b
-        url: https://huggingface.co/google/gemma-2-27b
-        precision: float16
-    - group: Cohere
-      tag: cohere
-      models:
-      - model: C4AI Command R+ 08-2024
-        mad_tag: pyt_vllm_c4ai-command-r-plus-08-2024
-        model_repo: CohereForAI/c4ai-command-r-plus-08-2024
-        url: https://huggingface.co/CohereForAI/c4ai-command-r-plus-08-2024
-        precision: float16
-      - model: C4AI Command R+ 08-2024 FP8
-        mad_tag: pyt_vllm_command-r-plus_fp8
-        model_repo: amd/c4ai-command-r-plus-FP8-KV
-        url: https://huggingface.co/amd/c4ai-command-r-plus-FP8-KV
-        precision: float8
-    - group: DeepSeek
-      tag: deepseek
-      models:
-      - model: DeepSeek MoE 16B
-        mad_tag: pyt_vllm_deepseek-moe-16b-chat
-        model_repo: deepseek-ai/deepseek-moe-16b-chat
-        url: https://huggingface.co/deepseek-ai/deepseek-moe-16b-chat
-        precision: float16
     - group: Microsoft Phi
       tag: phi
       models:
@@ -153,11 +86,3 @@ vllm_benchmark:
         mad_tag: pyt_vllm_phi-4
         model_repo: microsoft/phi-4
         url: https://huggingface.co/microsoft/phi-4
-    - group: TII Falcon
-      tag: falcon
-      models:
-      - model: Falcon 180B
-        mad_tag: pyt_vllm_falcon-180b
-        model_repo: tiiuae/falcon-180B
-        url: https://huggingface.co/tiiuae/falcon-180B
-        precision: float16

docs/data/how-to/rocm-for-ai/training/megatron-lm-benchmark-models.yaml

@@ -1,26 +1,15 @@
 dockers:
-  - pull_tag: rocm/megatron-lm:v25.6_py312
-    docker_hub_url: https://hub.docker.com/layers/rocm/megatron-lm/v25.6_py312/images/sha256-482ff906532285bceabdf2bda629bd32cb6174d2d07f4243a736378001b28df0
+  - pull_tag: rocm/megatron-lm:v25.7_py310
+    docker_hub_url: https://hub.docker.com/layers/rocm/megatron-lm/v25.7_py310/images/sha256-6189df849feeeee3ae31bb1e97aef5006d69d2b90c134e97708c19632e20ab5a
     components:
-      ROCm: 6.4.1
-      PyTorch: 2.8.0a0+git7d205b2
-      Python: 3.12
-      Transformer Engine: 2.1.0.dev0+8c4a512
-      hipBLASLt: 393e413
-      Triton: 3.3.0
-      RCCL: 2.23.4.7a84c5d
-    doc_name: Ubuntu 24.04 + Python 3.12
-  - pull_tag: rocm/megatron-lm:v25.6_py310
-    docker_hub_url: https://hub.docker.com/layers/rocm/megatron-lm/v25.6_py310/images/sha256-9627bd9378684fe26cb1a10c7dd817868f553b33402e49b058355b0f095568d6
-    components:
-      ROCm: 6.4.1
-      PyTorch: 2.8.0a0+git7d205b2
+      ROCm: 6.4.2
+      Primus: v0.1.0-rc1
+      PyTorch: 2.8.0a0+gitd06a406
       Python: "3.10"
-      Transformer Engine: 2.1.0.dev0+8c4a512
-      hipBLASLt: 393e413
+      Transformer Engine: 2.1.0.dev0+ba586519
+      hipBLASLt: 37ba1d36
       Triton: 3.3.0
-      RCCL: 2.23.4.7a84c5d
-    doc_name: Ubuntu 22.04 + Python 3.10
+      RCCL: 2.22.3
 model_groups:
   - group: Meta Llama
     tag: llama

docs/data/how-to/rocm-for-ai/training/previous-versions/megatron-lm-v25.6-benchmark-models.yaml

@@ -0,0 +1,60 @@
+dockers:
+  - pull_tag: rocm/megatron-lm:v25.6_py312
+    docker_hub_url: https://hub.docker.com/layers/rocm/megatron-lm/v25.6_py312/images/sha256-482ff906532285bceabdf2bda629bd32cb6174d2d07f4243a736378001b28df0
+    components:
+      ROCm: 6.4.1
+      PyTorch: 2.8.0a0+git7d205b2
+      Python: 3.12
+      Transformer Engine: 2.1.0.dev0+8c4a512
+      hipBLASLt: 393e413
+      Triton: 3.3.0
+      RCCL: 2.23.4.7a84c5d
+    doc_name: Ubuntu 24.04 + Python 3.12
+  - pull_tag: rocm/megatron-lm:v25.6_py310
+    docker_hub_url: https://hub.docker.com/layers/rocm/megatron-lm/v25.6_py310/images/sha256-9627bd9378684fe26cb1a10c7dd817868f553b33402e49b058355b0f095568d6
+    components:
+      ROCm: 6.4.1
+      PyTorch: 2.8.0a0+git7d205b2
+      Python: "3.10"
+      Transformer Engine: 2.1.0.dev0+8c4a512
+      hipBLASLt: 393e413
+      Triton: 3.3.0
+      RCCL: 2.23.4.7a84c5d
+    doc_name: Ubuntu 22.04 + Python 3.10
+model_groups:
+  - group: Meta Llama
+    tag: llama
+    models:
+      - model: Llama 3.3 70B
+        mad_tag: pyt_megatron_lm_train_llama-3.3-70b
+      - model: Llama 3.1 8B
+        mad_tag: pyt_megatron_lm_train_llama-3.1-8b
+      - model: Llama 3.1 70B
+        mad_tag: pyt_megatron_lm_train_llama-3.1-70b
+      - model: Llama 3.1 70B (proxy)
+        mad_tag: pyt_megatron_lm_train_llama-3.1-70b-proxy
+      - model: Llama 2 7B
+        mad_tag: pyt_megatron_lm_train_llama-2-7b
+      - model: Llama 2 70B
+        mad_tag: pyt_megatron_lm_train_llama-2-70b
+  - group: DeepSeek
+    tag: deepseek
+    models:
+      - model: DeepSeek-V3 (proxy)
+        mad_tag: pyt_megatron_lm_train_deepseek-v3-proxy
+      - model: DeepSeek-V2-Lite
+        mad_tag: pyt_megatron_lm_train_deepseek-v2-lite-16b
+  - group: Mistral AI
+    tag: mistral
+    models:
+      - model: Mixtral 8x7B
+        mad_tag: pyt_megatron_lm_train_mixtral-8x7b
+      - model: Mixtral 8x22B (proxy)
+        mad_tag: pyt_megatron_lm_train_mixtral-8x22b-proxy
+  - group: Qwen
+    tag: qwen
+    models:
+      - model: Qwen 2.5 7B
+        mad_tag: pyt_megatron_lm_train_qwen2.5-7b
+      - model: Qwen 2.5 72B
+        mad_tag: pyt_megatron_lm_train_qwen2.5-72b

docs/data/how-to/rocm-for-ai/training/primus-megatron-benchmark-models.yaml

@@ -0,0 +1,58 @@
+dockers:
+  - pull_tag: rocm/megatron-lm:v25.7_py310
+    docker_hub_url: https://hub.docker.com/layers/rocm/megatron-lm/v25.7_py310/images/sha256-6189df849feeeee3ae31bb1e97aef5006d69d2b90c134e97708c19632e20ab5a
+    components:
+      ROCm: 6.4.2
+      Primus: v0.1.0-rc1
+      PyTorch: 2.8.0a0+gitd06a406
+      Python: "3.10"
+      Transformer Engine: 2.1.0.dev0+ba586519
+      hipBLASLt: 37ba1d36
+      Triton: 3.3.0
+      RCCL: 2.22.3
+model_groups:
+  - group: Meta Llama
+    tag: llama
+    models:
+      - model: Llama 3.3 70B
+        mad_tag: primus_pyt_megatron_lm_train_llama-3.3-70b
+        config_name: llama3.3_70B-pretrain.yaml
+      - model: Llama 3.1 70B
+        mad_tag: primus_pyt_megatron_lm_train_llama-3.1-70b
+        config_name: llama3.1_70B-pretrain.yaml
+      - model: Llama 3.1 8B
+        mad_tag: primus_pyt_megatron_lm_train_llama-3.1-8b
+        config_name: llama3.1_8B-pretrain.yaml
+      - model: Llama 2 7B
+        mad_tag: primus_pyt_megatron_lm_train_llama-2-7b
+        config_name: llama2_7B-pretrain.yaml
+      - model: Llama 2 70B
+        mad_tag: primus_pyt_megatron_lm_train_llama-2-70b
+        config_name: llama2_70B-pretrain.yaml
+  - group: DeepSeek
+    tag: deepseek
+    models:
+      - model: DeepSeek-V3 (proxy)
+        mad_tag: primus_pyt_megatron_lm_train_deepseek-v3-proxy
+        config_name: deepseek_v3-pretrain.yaml
+      - model: DeepSeek-V2-Lite
+        mad_tag: primus_pyt_megatron_lm_train_deepseek-v2-lite-16b
+        config_name: deepseek_v2_lite-pretrain.yaml
+  - group: Mistral AI
+    tag: mistral
+    models:
+      - model: Mixtral 8x7B
+        mad_tag: primus_pyt_megatron_lm_train_mixtral-8x7b
+        config_name: mixtral_8x7B_v0.1-pretrain.yaml
+      - model: Mixtral 8x22B (proxy)
+        mad_tag: primus_pyt_megatron_lm_train_mixtral-8x22b-proxy
+        config_name: mixtral_8x22B_v0.1-pretrain.yaml
+  - group: Qwen
+    tag: qwen
+    models:
+      - model: Qwen 2.5 7B
+        mad_tag: primus_pyt_megatron_lm_train_qwen2.5-7b
+        config_name: primus_qwen2.5_7B-pretrain.yaml
+      - model: Qwen 2.5 72B
+        mad_tag: primus_pyt_megatron_lm_train_qwen2.5-72b
+        config_name: qwen2.5_72B-pretrain.yaml

docs/how-to/build-rocm.rst

@@ -19,5 +19,5 @@ The general steps to build ROCm are:
 #. Run the build command
 
 Because the ROCm stack is constantly evolving, the most current instructions are stored with the source code in GitHub.  
-For detailed build instructions, see `Build ROCm from source <https://github.com/ROCm/ROCm?tab=readme-ov-file#build-rocm-from-source>`_
+For detailed build instructions, see `Getting and Building ROCm from Source <https://github.com/ROCm/ROCm?tab=readme-ov-file#getting-and-building-rocm-from-source>`.
 

docs/how-to/deep-learning-rocm.rst

@@ -2,54 +2,132 @@
    :description: How to install deep learning frameworks for ROCm
    :keywords: deep learning, frameworks, ROCm, install, PyTorch, TensorFlow, JAX, MAGMA, DeepSpeed, ML, AI
 
-********************************************
-Installing deep learning frameworks for ROCm
-********************************************
+**********************************
+Deep learning frameworks for ROCm
+**********************************
 
-ROCm provides a comprehensive ecosystem for deep learning development, including
-:ref:`libraries <artificial-intelligence-apis>` for optimized deep learning operations and ROCm-aware versions of popular
-deep learning frameworks and libraries such as PyTorch, TensorFlow, and JAX. ROCm works closely with these
-frameworks to ensure that framework-specific optimizations take advantage of AMD accelerator and GPU architectures.
+Deep learning frameworks provide environments for machine learning, training, fine-tuning, inference, and performance optimization.
 
-The following guides provide information on compatibility and supported
-features for these ROCm-enabled deep learning frameworks.
+ROCm offers a complete ecosystem for developing and running deep learning applications efficiently. It also provides ROCm-compatible versions of popular frameworks and libraries, such as PyTorch, TensorFlow, JAX, and others.
 
-* :doc:`PyTorch compatibility <../compatibility/ml-compatibility/pytorch-compatibility>`
-* :doc:`TensorFlow compatibility <../compatibility/ml-compatibility/tensorflow-compatibility>`
-* :doc:`JAX compatibility <../compatibility/ml-compatibility/jax-compatibility>`
-* :doc:`verl compatibility <../compatibility/ml-compatibility/verl-compatibility>`
-* :doc:`Stanford Megatron-LM compatibility <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`
-* :doc:`DGL compatibility <../compatibility/ml-compatibility/dgl-compatibility>`
+The AMD ROCm organization actively contributes to open-source development and collaborates closely with framework organizations. This collaboration ensures that framework-specific optimizations effectively leverage AMD GPUs and accelerators.
 
-This chart steps through typical installation workflows for installing deep learning frameworks for ROCm.
+The table below summarizes information about ROCm-enabled deep learning frameworks. It includes details on ROCm compatibility and third-party tool support, installation steps and options, and links to GitHub resources. For a complete list of supported framework versions on ROCm, see the :doc:`Compatibility matrix <../compatibility/compatibility-matrix>` topic.
 
-.. image:: ../data/how-to/framework_install_2024_07_04.png
-   :alt: Flowchart for installing ROCm-aware machine learning frameworks
-   :align: center
+.. list-table:: 
+    :header-rows: 1
+    :widths: 5 3 6 3
 
-See the installation instructions to get started.
+    * - Framework
+      - Installation
+      - Installation options
+      - GitHub
 
-* :doc:`PyTorch for ROCm <rocm-install-on-linux:install/3rd-party/pytorch-install>`
-* :doc:`TensorFlow for ROCm <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
-* :doc:`JAX for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`
-* :doc:`verl for ROCm <rocm-install-on-linux:install/3rd-party/verl-install>`
-* :doc:`Stanford Megatron-LM for ROCm <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>`
-* :doc:`DGL for ROCm <rocm-install-on-linux:install/3rd-party/dgl-install>`
+    * - `PyTorch <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/pytorch-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-a-docker-image-with-pytorch-pre-installed>`_ 
+        - `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-a-wheels-package>`_
+        - `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-the-pytorch-rocm-base-docker-image>`_ 
+        - `Upstream Docker file <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-the-pytorch-upstream-dockerfile>`_
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/pytorch"><i class="fab fa-github fa-lg"></i></a>
+   
+    * - `TensorFlow <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/tensorflow-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html#using-a-docker-image-with-tensorflow-pre-installed>`_
+        - `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html#using-a-wheels-package>`_
 
-.. note::
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/tensorflow-upstream"><i class="fab fa-github fa-lg"></i></a> 
+
+    * - `JAX <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/jax-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/jax-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/jax-install.html#using-a-prebuilt-docker-image>`_
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/jax"><i class="fab fa-github fa-lg"></i></a>
+   
+    * - `verl <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/verl-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/verl-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/verl-install.html#use-a-prebuilt-docker-image-with-verl-pre-installed>`_
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/verl"><i class="fab fa-github fa-lg"></i></a>
+
+    * - `Stanford Megatron-LM <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/stanford-megatron-lm-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/stanford-megatron-lm-install.html#use-a-prebuilt-docker-image-with-stanford-megatron-lm-pre-installed>`_
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/Stanford-Megatron-LM"><i class="fab fa-github fa-lg"></i></a>
+   
+    * - `DGL <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/dgl-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/dgl-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/dgl-install.html#use-a-prebuilt-docker-image-with-dgl-pre-installed>`_
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/dgl"><i class="fab fa-github fa-lg"></i></a> 
+
+    * - `Megablocks <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/megablocks-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/megablocks-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/megablocks-install.html#using-a-prebuilt-docker-image-with-megablocks-pre-installed>`_
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/megablocks"><i class="fab fa-github fa-lg"></i></a>
+   
+    * - `Taichi <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/taichi-compatibility.html>`_
+      - .. raw:: html
+         
+          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html"><i class="fas fa-link fa-lg"></i></a>
+      - 
+        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html#use-a-prebuilt-docker-image-with-taichi-pre-installed>`_ 
+        - `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/taichi-install.html#use-a-wheels-package>`_
+
+      - .. raw:: html
+         
+          <a href="https://github.com/ROCm/taichi"><i class="fab fa-github fa-lg"></i></a>      
 
-   For guidance on installing ROCm itself, refer to :doc:`ROCm installation for Linux <rocm-install-on-linux:index>`.
 
 Learn how to use your ROCm deep learning environment for training, fine-tuning, inference, and performance optimization
 through the following guides.
 
 * :doc:`rocm-for-ai/index`
 
-* :doc:`Training <rocm-for-ai/training/index>`
+* :doc:`Use ROCm for training <rocm-for-ai/training/index>`
+
+* :doc:`Use ROCm for fine-tuning LLMs <rocm-for-ai/fine-tuning/index>`
+
+* :doc:`Use ROCm for AI inference <rocm-for-ai/inference/index>`
+
+* :doc:`Use ROCm for AI inference optimization <rocm-for-ai/inference-optimization/index>`
+
+
+
+
 
-* :doc:`Fine-tuning LLMs <rocm-for-ai/fine-tuning/index>`
 
-* :doc:`Inference <rocm-for-ai/inference/index>`
 
-* :doc:`Inference optimization <rocm-for-ai/inference-optimization/index>`
 

docs/how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/sglang-history.rst

@@ -0,0 +1,25 @@
+:orphan:
+
+****************************************************
+SGLang inference performance testing version history
+****************************************************
+
+This table lists previous versions of the ROCm SGLang inference performance
+testing environment. For detailed information about available models for
+benchmarking, see the version-specific documentation.
+
+.. list-table::
+   :header-rows: 1
+
+   * - Docker image tag
+     - Components
+     - Resources
+
+   * - ``lmsysorg/sglang:v0.4.5-rocm630``
+     - 
+       * ROCm 6.3.0
+       * SGLang 0.4.5
+       * PyTorch 2.6.0
+     - 
+       * :doc:`Documentation <../sglang>`
+       * `Docker Hub <https://hub.docker.com/layers/lmsysorg/sglang/v0.4.5-rocm630/images/sha256-63d2cb760a237125daf6612464cfe2f395c0784e21e8b0ea37d551cd10d3c951>`__

docs/how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-0.9.1-20250702.rst

@@ -14,7 +14,7 @@ vLLM inference performance testing
    This documentation does not reflect the latest version of ROCm vLLM
    inference performance documentation. See :doc:`../vllm` for the latest version.
 
-.. _vllm-benchmark-unified-docker:
+.. _vllm-benchmark-unified-docker-702:
 
 .. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/previous-versions/vllm_0.9.1_20250702-benchmark-models.yaml
 
@@ -77,7 +77,7 @@ vLLM inference performance testing
         </div>
       </div>
 
-   .. _vllm-benchmark-vllm:
+   .. _vllm-benchmark-vllm-702:
 
    {% for model_group in model_groups %}
       {% for model in model_group.models %}
@@ -159,7 +159,7 @@ vLLM inference performance testing
    Once the setup is complete, choose between two options to reproduce the
    benchmark results:
 
-   .. _vllm-benchmark-mad:
+   .. _vllm-benchmark-mad-702:
 
    {% for model_group in model_groups %}
       {% for model in model_group.models %}

docs/how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-0.9.1-20250715.rst

@@ -0,0 +1,450 @@
+:orphan:
+
+.. meta::
+   :description: Learn how to validate LLM inference performance on MI300X accelerators using AMD MAD and the
+                 ROCm vLLM Docker image.
+   :keywords: model, MAD, automation, dashboarding, validate
+
+**********************************
+vLLM inference performance testing
+**********************************
+
+.. caution::
+
+   This documentation does not reflect the latest version of ROCm vLLM
+   inference performance documentation. See :doc:`../vllm` for the latest version.
+
+.. _vllm-benchmark-unified-docker-715:
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/previous-versions/vllm_0.9.1_20250715-benchmark_models.yaml
+
+   {% set unified_docker = data.vllm_benchmark.unified_docker.latest %}
+   {% set model_groups = data.vllm_benchmark.model_groups %}
+
+   The `ROCm vLLM Docker <{{ unified_docker.docker_hub_url }}>`_ image offers
+   a prebuilt, optimized environment for validating large language model (LLM)
+   inference performance on AMD Instinct™ MI300X series accelerators. This ROCm vLLM
+   Docker image integrates vLLM and PyTorch tailored specifically for MI300X series
+   accelerators and includes the following components:
+
+   .. list-table::
+      :header-rows: 1
+
+      * - Software component
+        - Version
+
+      * - `ROCm <https://github.com/ROCm/ROCm>`__
+        - {{ unified_docker.rocm_version }}
+
+      * - `vLLM <https://docs.vllm.ai/en/latest>`__
+        - {{ unified_docker.vllm_version }}
+
+      * - `PyTorch <https://github.com/ROCm/pytorch>`__
+        - {{ unified_docker.pytorch_version }}
+
+      * - `hipBLASLt <https://github.com/ROCm/hipBLASLt>`__
+        - {{ unified_docker.hipblaslt_version }}
+
+With this Docker image, you can quickly test the :ref:`expected
+inference performance numbers <vllm-benchmark-performance-measurements>` for
+MI300X series accelerators.
+
+What's new
+==========
+
+The following is summary of notable changes since the :doc:`previous ROCm/vLLM Docker release <vllm-history>`.
+
+* The ``--compilation-config-parameter`` is no longer required as its options are now enabled by default.
+  This parameter has been removed from the benchmarking script.
+
+* Resolved Llama 3.1 405 B custom all-reduce issue, eliminating the need for ``--disable-custom-all-reduce``.
+  This parameter has been removed from the benchmarking script.
+
+* Fixed a ``+rms_norm`` custom kernel issue.
+
+* Added quick reduce functionality. Set ``VLLM_ROCM_QUICK_REDUCE_QUANTIZATION=FP`` to enable; supported modes are ``FP``, ``INT8``, ``INT6``, ``INT4``.
+
+* Implemented a workaround to potentially mitigate GPU crashes experienced with the Command R+ model, pending a driver fix.
+
+Supported models
+================
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/previous-versions/vllm_0.9.1_20250715-benchmark_models.yaml
+
+   {% set unified_docker = data.vllm_benchmark.unified_docker.latest %}
+   {% set model_groups = data.vllm_benchmark.model_groups %}
+
+   .. _vllm-benchmark-available-models-715:
+
+   The following models are supported for inference performance benchmarking
+   with vLLM and ROCm. Some instructions, commands, and recommendations in this
+   documentation might vary by model -- select one to get started.
+
+   .. raw:: html
+
+      <div id="vllm-benchmark-ud-params-picker" class="container-fluid">
+      <div class="row">
+         <div class="col-2 me-2 model-param-head">Model group</div>
+         <div class="row col-10">
+   {% for model_group in model_groups %}
+            <div class="col-3 model-param" data-param-k="model-group" data-param-v="{{ model_group.tag }}" tabindex="0">{{ model_group.group }}</div>
+   {% endfor %}
+         </div>
+      </div>
+
+      <div class="row mt-1">
+         <div class="col-2 me-2 model-param-head">Model</div>
+         <div class="row col-10">
+   {% for model_group in model_groups %}
+      {% set models = model_group.models %}
+      {% for model in models %}
+         {% if models|length % 3 == 0 %}
+            <div class="col-4 model-param" data-param-k="model" data-param-v="{{ model.mad_tag }}" data-param-group="{{ model_group.tag }}" tabindex="0">{{ model.model }}</div>
+         {% else %}
+            <div class="col-6 model-param" data-param-k="model" data-param-v="{{ model.mad_tag }}" data-param-group="{{ model_group.tag }}" tabindex="0">{{ model.model }}</div>
+         {% endif %}
+      {% endfor %}
+   {% endfor %}
+         </div>
+      </div>
+      </div>
+
+   .. _vllm-benchmark-vllm-715:
+
+   {% for model_group in model_groups %}
+      {% for model in model_group.models %}
+
+   .. container:: model-doc {{model.mad_tag}}
+
+      .. note::
+
+         See the `{{ model.model }} model card on Hugging Face <{{ model.url }}>`_ to learn more about your selected model.
+         Some models require access authorization prior to use via an external license agreement through a third party.
+
+      {% endfor %}
+   {% endfor %}
+
+.. note::
+
+   vLLM is a toolkit and library for LLM inference and serving. AMD implements
+   high-performance custom kernels and modules in vLLM to enhance performance.
+   See :ref:`fine-tuning-llms-vllm` and :ref:`mi300x-vllm-optimization` for
+   more information.
+
+.. _vllm-benchmark-performance-measurements-715:
+
+Performance measurements
+========================
+
+To evaluate performance, the
+`Performance results with AMD ROCm software <https://www.amd.com/en/developer/resources/rocm-hub/dev-ai/performance-results.html>`_
+page provides reference throughput and latency measurements for inferencing popular AI models.
+
+.. important::
+
+   The performance data presented in
+   `Performance results with AMD ROCm software <https://www.amd.com/en/developer/resources/rocm-hub/dev-ai/performance-results.html>`_
+   only reflects the latest version of this inference benchmarking environment.
+   The listed measurements should not be interpreted as the peak performance achievable by AMD Instinct MI325X and MI300X accelerators or ROCm software.
+
+System validation
+=================
+
+Before running AI workloads, it's important to validate that your AMD hardware is configured
+correctly and performing optimally.
+
+If you have already validated your system settings, including aspects like NUMA auto-balancing, you
+can skip this step. Otherwise, complete the procedures in the :ref:`System validation and
+optimization <rocm-for-ai-system-optimization>` guide to properly configure your system settings
+before starting training.
+
+To test for optimal performance, consult the recommended :ref:`System health benchmarks
+<rocm-for-ai-system-health-bench>`. This suite of tests will help you verify and fine-tune your
+system's configuration.
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/previous-versions/vllm_0.9.1_20250715-benchmark_models.yaml
+
+   {% set unified_docker = data.vllm_benchmark.unified_docker.latest %}
+   {% set model_groups = data.vllm_benchmark.model_groups %}
+
+   Pull the Docker image
+   =====================
+
+   Download the `ROCm vLLM Docker image <{{ unified_docker.docker_hub_url }}>`_.
+   Use the following command to pull the Docker image from Docker Hub.
+
+   .. code-block:: shell
+
+      docker pull {{ unified_docker.pull_tag }}
+
+   Benchmarking
+   ============
+
+   Once the setup is complete, choose between two options to reproduce the
+   benchmark results:
+
+   .. _vllm-benchmark-mad-715:
+
+   {% for model_group in model_groups %}
+      {% for model in model_group.models %}
+
+   .. container:: model-doc {{model.mad_tag}}
+
+      .. tab-set::
+
+         .. tab-item:: MAD-integrated benchmarking
+
+            1. Clone the ROCm Model Automation and Dashboarding (`<https://github.com/ROCm/MAD>`__) repository to a local
+               directory and install the required packages on the host machine.
+
+               .. code-block:: shell
+
+                  git clone https://github.com/ROCm/MAD
+                  cd MAD
+                  pip install -r requirements.txt
+
+            2. Use this command to run the performance benchmark test on the `{{model.model}} <{{ model.url }}>`_ model
+               using one GPU with the :literal:`{{model.precision}}` data type on the host machine.
+
+               .. code-block:: shell
+
+                  export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
+                  madengine run \
+                      --tags {{model.mad_tag}} \
+                      --keep-model-dir \
+                      --live-output \
+                      --timeout 28800
+
+            MAD launches a Docker container with the name
+            ``container_ci-{{model.mad_tag}}``. The latency and throughput reports of the
+            model are collected in the following path: ``~/MAD/reports_{{model.precision}}/``.
+
+            Although the :ref:`available models <vllm-benchmark-available-models>` are preconfigured
+            to collect latency and throughput performance data, you can also change the benchmarking
+            parameters. See the standalone benchmarking tab for more information.
+
+            {% if model.tunableop %}
+
+            .. note::
+
+               For improved performance, consider enabling :ref:`PyTorch TunableOp <mi300x-tunableop>`.
+               TunableOp automatically explores different implementations and configurations of certain PyTorch
+               operators to find the fastest one for your hardware.
+
+               By default, ``{{model.mad_tag}}`` runs with TunableOp disabled
+               (see
+               `<https://github.com/ROCm/MAD/blob/develop/models.json>`__).
+               To enable it, include the ``--tunableop on`` argument in your
+               run.
+
+               Enabling TunableOp triggers a two-pass run -- a warm-up followed
+               by the performance-collection run.
+
+            {% endif %}
+
+         .. tab-item:: Standalone benchmarking
+
+            .. rubric:: Download the Docker image and required scripts
+
+            1. Run the vLLM benchmark tool independently by starting the
+               `Docker container <{{ unified_docker.docker_hub_url }}>`_
+               as shown in the following snippet.
+
+               .. code-block:: shell
+
+                  docker pull {{ unified_docker.pull_tag }}
+                  docker run -it \
+                      --device=/dev/kfd \
+                      --device=/dev/dri \
+                      --group-add video \
+                      --shm-size 16G \
+                      --security-opt seccomp=unconfined \
+                      --security-opt apparmor=unconfined \
+                      --cap-add=SYS_PTRACE \
+                      -v $(pwd):/workspace \
+                      --env HUGGINGFACE_HUB_CACHE=/workspace \
+                      --name test \
+                      {{ unified_docker.pull_tag }}
+
+            2. In the Docker container, clone the ROCm MAD repository and navigate to the
+               benchmark scripts directory at ``~/MAD/scripts/vllm``.
+
+               .. code-block:: shell
+
+                  git clone https://github.com/ROCm/MAD
+                  cd MAD/scripts/vllm
+
+            3. To start the benchmark, use the following command with the appropriate options.
+
+               .. dropdown:: Benchmark options
+                  :open:
+
+                  .. list-table::
+                     :header-rows: 1
+                     :align: center
+
+                     * - Name
+                       - Options
+                       - Description
+
+                     * - ``$test_option``
+                       - latency
+                       - Measure decoding token latency
+
+                     * -
+                       - throughput
+                       - Measure token generation throughput
+
+                     * -
+                       - all
+                       - Measure both throughput and latency
+
+                     * - ``$num_gpu``
+                       - 1 or 8
+                       - Number of GPUs
+
+                     * - ``$datatype``
+                       - ``float16`` or ``float8``
+                       - Data type
+
+                  The input sequence length, output sequence length, and tensor parallel (TP) are
+                  already configured. You don't need to specify them with this script.
+
+               Command:
+
+               .. code-block::
+
+                  ./vllm_benchmark_report.sh \
+                      -s $test_option \
+                      -m {{model.model_repo}} \
+                      -g $num_gpu \
+                      -d {{model.precision}}
+
+               .. note::
+
+                  For best performance, it's recommend to run with ``VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1``.
+
+                  If you encounter the following error, pass your access-authorized Hugging
+                  Face token to the gated models.
+
+                  .. code-block::
+
+                     OSError: You are trying to access a gated repo.
+
+                     # pass your HF_TOKEN
+                     export HF_TOKEN=$your_personal_hf_token
+
+            .. rubric:: Benchmarking examples
+
+            Here are some examples of running the benchmark with various options:
+
+            * Latency benchmark
+
+              Use this command to benchmark the latency of the {{model.model}} model on eight GPUs with :literal:`{{model.precision}}` precision.
+
+              .. code-block::
+
+                 ./vllm_benchmark_report.sh \
+                     -s latency \
+                     -m {{model.model_repo}} \
+                     -g 8 \
+                     -d {{model.precision}}
+
+              Find the latency report at ``./reports_{{model.precision}}_vllm_rocm{{unified_docker.rocm_version}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_latency_report.csv``.
+
+            * Throughput benchmark
+
+              Use this command to benchmark the throughput of the {{model.model}} model on eight GPUs with :literal:`{{model.precision}}` precision.
+
+              .. code-block:: shell
+
+                 ./vllm_benchmark_report.sh \
+                     -s throughput \
+                     -m {{model.model_repo}} \
+                     -g 8 \
+                     -d {{model.precision}}
+
+              Find the throughput report at ``./reports_{{model.precision}}_vllm_rocm{{unified_docker.rocm_version}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_throughput_report.csv``.
+
+            .. raw:: html
+
+               <style>
+               mjx-container[jax="CHTML"][display="true"] {
+                  text-align: left;
+                  margin: 0;
+               }
+               </style>
+
+            .. note::
+
+               Throughput is calculated as:
+
+               - .. math:: throughput\_tot = requests \times (\mathsf{\text{input lengths}} + \mathsf{\text{output lengths}}) / elapsed\_time
+
+               - .. math:: throughput\_gen = requests \times \mathsf{\text{output lengths}} / elapsed\_time
+      {% endfor %}
+   {% endfor %}
+
+Advanced usage
+==============
+
+For information on experimental features and known issues related to ROCm optimization efforts on vLLM,
+see the developer's guide at `<https://github.com/ROCm/vllm/tree/f94ec9beeca1071cc34f9d1e206d8c7f3ac76129/docs/dev-docker>`__.
+
+Reproducing the Docker image
+----------------------------
+
+To reproduce this ROCm/vLLM Docker image release, follow these steps:
+
+1. Clone the `vLLM repository <https://github.com/ROCm/vllm>`__.
+
+   .. code-block:: shell
+
+      git clone https://github.com/ROCm/vllm.git
+
+2. Checkout the specific release commit.
+
+   .. code-block:: shell
+
+      cd vllm
+      git checkout b432b7a285aa0dcb9677380936ffa74931bb6d6f
+
+3. Build the Docker image. Replace ``vllm-rocm`` with your desired image tag.
+
+   .. code-block:: shell
+
+      docker build -f docker/Dockerfile.rocm -t vllm-rocm .
+
+Known issues and workarounds
+============================
+
+AITER does not support FP8 KV cache yet.
+
+Further reading
+===============
+
+- To learn more about the options for latency and throughput benchmark scripts,
+  see `<https://github.com/ROCm/vllm/tree/main/benchmarks>`_.
+
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
+- To learn more about system settings and management practices to configure your system for
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
+
+- For application performance optimization strategies for HPC and AI workloads,
+  including inference with vLLM, see :doc:`/how-to/rocm-for-ai/inference-optimization/workload`.
+
+- To learn how to run community models from Hugging Face on AMD GPUs, see
+  :doc:`Running models from Hugging Face </how-to/rocm-for-ai/inference/hugging-face-models>`.
+
+- To learn how to fine-tune LLMs and optimize inference, see
+  :doc:`Fine-tuning LLMs and inference optimization </how-to/rocm-for-ai/fine-tuning/fine-tuning-and-inference>`.
+
+- For a list of other ready-made Docker images for AI with ROCm, see
+  `AMD Infinity Hub <https://www.amd.com/en/developer/resources/infinity-hub.html#f-amd_hub_category=AI%20%26%20ML%20Models>`_.
+
+Previous versions
+=================
+
+See :doc:`vllm-history` to find documentation for previous releases
+of the ``ROCm/vllm`` Docker image.

docs/how-to/rocm-for-ai/inference/benchmark-docker/previous-versions/vllm-history.rst

@@ -16,14 +16,23 @@ previous releases of the ``ROCm/vllm`` Docker image on `Docker Hub <https://hub.
      - Components
      - Resources
 
-   * - ``rocm/vllm:rocm6.4.1_vllm_0.9.1_20250715``
+   * - ``rocm/vllm:rocm6.4.1_vllm_0.10.0_20250812``
        (latest)
+     - 
+       * ROCm 6.4.1
+       * vLLM 0.10.0
+       * PyTorch 2.7.0
+     - 
+       * :doc:`Documentation <../vllm>`
+       * `Docker Hub <https://hub.docker.com/layers/rocm/vllm/rocm6.4.1_vllm_0.10.0_20250812/images/sha256-4c277ad39af3a8c9feac9b30bf78d439c74d9b4728e788a419d3f1d0c30cacaa>`__
+
+   * - ``rocm/vllm:rocm6.4.1_vllm_0.9.1_20250715``
      - 
        * ROCm 6.4.1
        * vLLM 0.9.1
        * PyTorch 2.7.0
      - 
-       * :doc:`Documentation <../vllm>`
+       * :doc:`Documentation <vllm-0.9.1-20250715>`
        * `Docker Hub <https://hub.docker.com/layers/rocm/vllm/rocm6.4.1_vllm_0.9.1_20250715/images/sha256-4a429705fa95a58f6d20aceab43b1b76fa769d57f32d5d28bd3f4e030e2a78ea>`__
 
    * - ``rocm/vllm:rocm6.4.1_vllm_0.9.1_20250702``

docs/how-to/rocm-for-ai/inference/benchmark-docker/pytorch-inference.rst

@@ -103,7 +103,7 @@ PyTorch inference performance testing
 
          The Chai-1 benchmark uses a specifically selected Docker image using ROCm 6.2.3 and PyTorch 2.3.0 to address an accuracy issue.
 
-   .. container:: model-doc pyt_clip_inference pyt_mochi_video_inference pyt_wan2.1_inference
+   .. container:: model-doc pyt_clip_inference pyt_mochi_video_inference pyt_wan2.1_inference pyt_janus_pro_inference pyt_hy_video
 
       Use the following command to pull the `ROCm PyTorch Docker image <https://hub.docker.com/layers/rocm/pytorch/latest/images/sha256-05b55983e5154f46e7441897d0908d79877370adca4d1fff4899d9539d6c4969>`__ from Docker Hub.
 
@@ -140,22 +140,27 @@ PyTorch inference performance testing
       .. code-block:: shell
 
          export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
-         python3 tools/run_models.py --tags {{model.mad_tag}} --keep-model-dir --live-output --timeout 28800
+         madengine run \
+             --tags {{model.mad_tag}} \
+             --keep-model-dir \
+             --live-output \
+             --timeout 28800
 
       MAD launches a Docker container with the name
       ``container_ci-{{model.mad_tag}}``. The latency and throughput reports of the
-      model are collected in ``perf.csv``.
+      model are collected in ``perf_{{model.mad_tag}}.csv``.
 
+      {% if model.mad_tag != "pyt_janus_pro_inference" %}
       .. note::
 
          For improved performance, consider enabling TunableOp. By default,
          ``{{model.mad_tag}}`` runs with TunableOp disabled (see
          `<https://github.com/ROCm/MAD/blob/develop/models.json>`__). To enable
-         it, edit the default run behavior in the ``tools/run_models.py``-- update the model's
-         run ``args`` by changing ``--tunableop off`` to ``--tunableop on``.
+         it, include the ``--tunableop on`` argument in your run.
 
          Enabling TunableOp triggers a two-pass run -- a warm-up followed by the performance-collection run.
          Although this might increase the initial training time, it can result in a performance gain.
+      {% endif %}
 
       {% endfor %}
    {% endfor %}
@@ -163,8 +168,10 @@ PyTorch inference performance testing
 Further reading
 ===============
 
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
 - To learn more about system settings and management practices to configure your system for
-  MI300X accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
 
 - For application performance optimization strategies for HPC and AI workloads,
   including inference with vLLM, see :doc:`../../inference-optimization/workload`.

docs/how-to/rocm-for-ai/inference/benchmark-docker/sglang.rst

@@ -0,0 +1,280 @@
+.. meta::
+   :description: Learn how to validate LLM inference performance on MI300X accelerators using AMD MAD and SGLang
+   :keywords: model, MAD, automation, dashboarding, validate
+
+************************************
+SGLang inference performance testing
+************************************
+
+.. _sglang-benchmark-unified-docker:
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/sglang-benchmark-models.yaml
+
+   {% set unified_docker = data.sglang_benchmark.unified_docker.latest %}
+
+   `SGLang <https://docs.sglang.ai>`__ is a high-performance inference and
+   serving engine for large language models (LLMs) and vision models. The
+   ROCm-enabled `SGLang Docker image <{{ unified_docker.docker_hub_url }}>`__
+   bundles SGLang with PyTorch, optimized for AMD Instinct MI300X series
+   accelerators. It includes the following software components:
+
+   .. list-table::
+      :header-rows: 1
+
+      * - Software component
+        - Version
+
+      * - `ROCm <https://github.com/ROCm/ROCm>`__
+        - {{ unified_docker.rocm_version }}
+
+      * - `SGLang <https://docs.sglang.ai/index.html>`__
+        - {{ unified_docker.sglang_version }} 
+
+      * - `PyTorch <https://github.com/pytorch/pytorch>`__
+        - {{ unified_docker.pytorch_version }} 
+
+System validation
+=================
+
+Before running AI workloads, it's important to validate that your AMD hardware is configured
+correctly and performing optimally.
+
+If you have already validated your system settings, including aspects like NUMA auto-balancing, you
+can skip this step. Otherwise, complete the procedures in the :ref:`System validation and
+optimization <rocm-for-ai-system-optimization>` guide to properly configure your system settings
+before starting training.
+
+To test for optimal performance, consult the recommended :ref:`System health benchmarks
+<rocm-for-ai-system-health-bench>`. This suite of tests will help you verify and fine-tune your
+system's configuration.
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/sglang-benchmark-models.yaml
+
+   {% set unified_docker = data.sglang_benchmark.unified_docker.latest %}
+   {% set model_groups = data.sglang_benchmark.model_groups %}
+
+   Pull the Docker image
+   =====================
+
+   Download the `SGLang Docker image <{{ unified_docker.docker_hub_url }}>`__.
+   Use the following command to pull the Docker image from Docker Hub.
+
+   .. code-block:: shell
+
+      docker pull {{ unified_docker.pull_tag }}
+
+   Benchmarking
+   ============
+
+   Once the setup is complete, choose one of the following methods to benchmark inference performance with
+   `DeepSeek-R1-Distill-Qwen-32B <https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-32B>`__.
+
+   .. _sglang-benchmark-mad:
+
+   {% for model_group in model_groups %}
+      {% for model in model_group.models %}
+
+   .. container:: model-doc {{model.mad_tag}}
+
+      .. tab-set::
+
+         .. tab-item:: MAD-integrated benchmarking
+
+            1. Clone the ROCm Model Automation and Dashboarding (`<https://github.com/ROCm/MAD>`__) repository to a local
+               directory and install the required packages on the host machine.
+
+               .. code-block:: shell
+
+                  git clone https://github.com/ROCm/MAD
+                  cd MAD
+                  pip install -r requirements.txt
+
+            2. Use this command to run the performance benchmark test on the `{{model.model}} <{{ model.url }}>`_ model
+               using one GPU with the ``{{model.precision}}`` data type on the host machine.
+
+               .. code-block:: shell
+
+                  export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
+                  madengine run \
+                      --tags {{model.mad_tag}} \
+                      --keep-model-dir \
+                      --live-output \
+                      --timeout 28800
+
+            MAD launches a Docker container with the name
+            ``container_ci-{{model.mad_tag}}``. The latency and throughput reports of the
+            model are collected in the following path: ``~/MAD/perf_DeepSeek-R1-Distill-Qwen-32B.csv``.
+
+            Although the DeepSeek-R1-Distill-Qwen-32B is preconfigured
+            to collect latency and throughput performance data, you can also change the benchmarking
+            parameters. See the standalone benchmarking tab for more information.
+
+         .. tab-item:: Standalone benchmarking
+
+            .. rubric:: Download the Docker image and required scripts
+
+            1. Run the SGLang benchmark script independently by starting the
+               `Docker container <{{ unified_docker.docker_hub_url }}>`__
+               as shown in the following snippet.
+
+               .. code-block:: shell
+
+                  docker pull {{ unified_docker.pull_tag }}
+                  docker run -it \
+                      --device=/dev/kfd \
+                      --device=/dev/dri \
+                      --group-add video \
+                      --shm-size 16G \
+                      --security-opt seccomp=unconfined \
+                      --security-opt apparmor=unconfined \
+                      --cap-add=SYS_PTRACE \
+                      -v $(pwd):/workspace \
+                      --env HUGGINGFACE_HUB_CACHE=/workspace \
+                      --name test \
+                      {{ unified_docker.pull_tag }}
+
+            2. In the Docker container, clone the ROCm MAD repository and navigate to the
+               benchmark scripts directory at ``~/MAD/scripts/sglang``.
+
+               .. code-block:: shell
+
+                  git clone https://github.com/ROCm/MAD
+                  cd MAD/scripts/sglang
+
+            3. To start the benchmark, use the following command with the appropriate options.
+
+               .. dropdown:: Benchmark options
+                  :open:
+
+                  .. list-table::
+                     :header-rows: 1
+                     :align: center
+
+                     * - Name
+                       - Options
+                       - Description
+
+                     * - ``$test_option``
+                       - latency
+                       - Measure decoding token latency
+
+                     * -
+                       - throughput
+                       - Measure token generation throughput
+
+                     * -
+                       - all
+                       - Measure both throughput and latency
+
+                     * - ``$num_gpu``
+                       - 8
+                       - Number of GPUs
+
+                     * - ``$datatype``
+                       - ``bfloat16``
+                       - Data type
+
+                     * - ``$dataset``
+                       - random
+                       - Dataset
+
+                  The input sequence length, output sequence length, and tensor parallel (TP) are
+                  already configured. You don't need to specify them with this script.
+
+               Command:
+
+               .. code-block:: shell
+
+                  ./sglang_benchmark_report.sh -s $test_option -m {{model.model_repo}} -g $num_gpu -d $datatype [-a $dataset]
+
+            .. note::
+
+               If you encounter the following error, pass your access-authorized Hugging
+               Face token to the gated models.
+
+               .. code-block:: shell-session
+
+                  OSError: You are trying to access a gated repo.
+                  # pass your HF_TOKEN
+                  export HF_TOKEN=$your_personal_hf_token
+
+            .. rubric:: Benchmarking examples
+
+            Here are some examples of running the benchmark with various options:
+
+            * Latency benchmark
+
+              Use this command to benchmark the latency of the {{model.model}} model on eight GPUs with ``{{model.precision}}`` precision.
+
+              .. code-block:: shell
+
+                 ./sglang_benchmark_report.sh \
+                     -s latency \
+                     -m {{model.model_repo}} \
+                     -g 8 \
+                     -d {{model.precision}}
+
+              Find the latency report at ``./reports_{{model.precision}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_latency_report.csv``.
+
+            * Throughput benchmark
+
+              Use this command to benchmark the throughput of the {{model.model}} model on eight GPUs with ``{{model.precision}}`` precision.
+
+              .. code-block:: shell
+
+                 ./sglang_benchmark_report.sh \
+                     -s throughput \
+                     -m {{model.model_repo}} \
+                     -g 8 \
+                     -d {{model.precision}} \
+                     -a random
+
+              Find the throughput report at ``./reports_{{model.precision}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_throughput_report.csv``.
+
+            .. raw:: html
+
+               <style>
+               mjx-container[jax="CHTML"][display="true"] {
+                  text-align: left;
+                  margin: 0;
+               }
+               </style>
+
+            .. note::
+
+               Throughput is calculated as:
+
+               - .. math:: throughput\_tot = requests \times (\mathsf{\text{input lengths}} + \mathsf{\text{output lengths}}) / elapsed\_time
+
+               - .. math:: throughput\_gen = requests \times \mathsf{\text{output lengths}} / elapsed\_time
+      {% endfor %}
+   {% endfor %}
+
+Further reading
+===============
+
+- To learn more about the options for latency and throughput benchmark scripts,
+  see `<https://github.com/sgl-project/sglang/tree/main/benchmark/blog_v0_2>`__.
+
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
+- To learn more about system settings and management practices to configure your system for
+  MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`__.
+
+- For application performance optimization strategies for HPC and AI workloads,
+  including inference with vLLM, see :doc:`/how-to/rocm-for-ai/inference-optimization/workload`.
+
+- To learn how to run community models from Hugging Face on AMD GPUs, see
+  :doc:`Running models from Hugging Face </how-to/rocm-for-ai/inference/hugging-face-models>`.
+
+- To learn how to fine-tune LLMs and optimize inference, see
+  :doc:`Fine-tuning LLMs and inference optimization </how-to/rocm-for-ai/fine-tuning/fine-tuning-and-inference>`.
+
+- For a list of other ready-made Docker images for AI with ROCm, see
+  `AMD Infinity Hub <https://www.amd.com/en/developer/resources/infinity-hub.html#f-amd_hub_category=AI%20%26%20ML%20Models>`_.
+
+Previous versions
+=================
+
+See :doc:`previous-versions/sglang-history` to find documentation for previous releases
+of SGLang inference performance testing.

docs/how-to/rocm-for-ai/inference/benchmark-docker/vllm.rst

@@ -7,7 +7,7 @@
 vLLM inference performance testing
 **********************************
 
-.. _vllm-benchmark-unified-docker:
+.. _vllm-benchmark-unified-docker-812:
 
 .. datatemplate:yaml:: /data/how-to/rocm-for-ai/inference/vllm-benchmark-models.yaml
 
@@ -47,17 +47,11 @@ What's new
 
 The following is summary of notable changes since the :doc:`previous ROCm/vLLM Docker release <previous-versions/vllm-history>`.
 
-* The ``--compilation-config-parameter`` is no longer required as its options are now enabled by default.
-  This parameter has been removed from the benchmarking script.
+* Upgraded to vLLM v0.10.
 
-* Resolved Llama 3.1 405 B custom all-reduce issue, eliminating the need for ``--disable-custom-all-reduce``.
-  This parameter has been removed from the benchmarking script.
+* FP8 KV cache support via AITER.
 
-* Fixed a ``+rms_norm`` custom kernel issue.
-
-* Added quick reduce functionality. Set ``VLLM_ROCM_QUICK_REDUCE_QUANTIZATION=FP`` to enable; supported modes are ``FP``, ``INT8``, ``INT6``, ``INT4``.
-
-* Implemented a workaround to potentially mitigate GPU crashes experienced with the Command R+ model, pending a driver fix.
+* Full graph capture support via AITER.
 
 Supported models
 ================
@@ -67,7 +61,7 @@ Supported models
    {% set unified_docker = data.vllm_benchmark.unified_docker.latest %}
    {% set model_groups = data.vllm_benchmark.model_groups %}
 
-   .. _vllm-benchmark-available-models:
+   .. _vllm-benchmark-available-models-812:
 
    The following models are supported for inference performance benchmarking
    with vLLM and ROCm. Some instructions, commands, and recommendations in this
@@ -102,7 +96,7 @@ Supported models
       </div>
       </div>
 
-   .. _vllm-benchmark-vllm:
+   .. _vllm-benchmark-vllm-812:
 
    {% for model_group in model_groups %}
       {% for model in model_group.models %}
@@ -124,14 +118,14 @@ Supported models
    See :ref:`fine-tuning-llms-vllm` and :ref:`mi300x-vllm-optimization` for
    more information.
 
-.. _vllm-benchmark-performance-measurements:
+.. _vllm-benchmark-performance-measurements-812:
 
 Performance measurements
 ========================
 
 To evaluate performance, the
 `Performance results with AMD ROCm software <https://www.amd.com/en/developer/resources/rocm-hub/dev-ai/performance-results.html>`_
-page provides reference throughput and latency measurements for inferencing popular AI models.
+page provides reference throughput and serving measurements for inferencing popular AI models.
 
 .. important::
 
@@ -176,7 +170,7 @@ system's configuration.
    Once the setup is complete, choose between two options to reproduce the
    benchmark results:
 
-   .. _vllm-benchmark-mad:
+   .. _vllm-benchmark-mad-812:
 
    {% for model_group in model_groups %}
       {% for model in model_group.models %}
@@ -202,19 +196,22 @@ system's configuration.
                .. code-block:: shell
 
                   export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
-                  python3 tools/run_models.py \
+                  madengine run \
                       --tags {{model.mad_tag}} \
                       --keep-model-dir \
                       --live-output \
                       --timeout 28800
 
             MAD launches a Docker container with the name
-            ``container_ci-{{model.mad_tag}}``. The latency and throughput reports of the
-            model are collected in the following path: ``~/MAD/reports_{{model.precision}}/``.
+            ``container_ci-{{model.mad_tag}}``. The throughput and serving reports of the
+            model are collected in the following paths: ``{{ model.mad_tag }}_throughput.csv``
+            and ``{{ model.mad_tag }}_serving.csv``.
 
-            Although the :ref:`available models <vllm-benchmark-available-models>` are preconfigured
-            to collect latency and throughput performance data, you can also change the benchmarking
-            parameters. See the standalone benchmarking tab for more information.
+            Although the :ref:`available models
+            <vllm-benchmark-available-models>` are preconfigured to collect
+            offline throughput and online serving performance data, you can
+            also change the benchmarking parameters. See the standalone
+            benchmarking tab for more information.
 
             {% if model.tunableop %}
 
@@ -224,14 +221,12 @@ system's configuration.
                TunableOp automatically explores different implementations and configurations of certain PyTorch
                operators to find the fastest one for your hardware.
 
-               By default, ``{{model.mad_tag}}`` runs with TunableOp disabled
-               (see
-               `<https://github.com/ROCm/MAD/blob/develop/models.json>`__). To
-               enable it, edit the default run behavior in the ``models.json``
-               configuration before running inference -- update the model's run
-               ``args`` by changing ``--tunableop off`` to ``--tunableop on``.
+               By default, ``{{model.mad_tag}}`` runs with TunableOp disabled (see
+               `<https://github.com/ROCm/MAD/blob/develop/models.json>`__). To enable it, include
+               the ``--tunableop on`` argument in your run.
 
-               Enabling TunableOp triggers a two-pass run -- a warm-up followed by the performance-collection run.
+               Enabling TunableOp triggers a two-pass run -- a warm-up followed by the
+               performance-collection run.
 
             {% endif %}
 
@@ -269,6 +264,13 @@ system's configuration.
 
             3. To start the benchmark, use the following command with the appropriate options.
 
+               .. code-block::
+
+                  ./run.sh \
+                      --config $CONFIG_CSV \
+                      --model_repo {{ model.model_repo }} \
+                      <overrides>
+
                .. dropdown:: Benchmark options
                   :open:
 
@@ -280,42 +282,40 @@ system's configuration.
                        - Options
                        - Description
 
-                     * - ``$test_option``
-                       - latency
-                       - Measure decoding token latency
+                     * - ``--config``
+                       - ``configs/default.csv``
+                       - Run configs from the CSV for the chosen model repo and benchmark.
 
                      * -
-                       - throughput
-                       - Measure token generation throughput
+                       - ``configs/extended.csv``
+                       - 
 
                      * -
-                       - all
-                       - Measure both throughput and latency
+                       - ``configs/performance.csv``
+                       - 
 
-                     * - ``$num_gpu``
-                       - 1 or 8
-                       - Number of GPUs
+                     * - ``--benchmark``
+                       - ``throughput``
+                       - Measure offline end-to-end throughput.
 
-                     * - ``$datatype``
-                       - ``float16`` or ``float8``
-                       - Data type
+                     * - 
+                       - ``serving``
+                       - Measure online serving performance.
+
+                     * - 
+                       - ``all``
+                       - Measure both throughput and serving.
+
+                     * - `<overrides>`
+                       - See `run.sh <https://github.com/ROCm/MAD/blob/develop/scripts/vllm/run.sh>`__ for more info.
+                       - Additional overrides to the config CSV.
 
                   The input sequence length, output sequence length, and tensor parallel (TP) are
                   already configured. You don't need to specify them with this script.
 
-               Command:
-
-               .. code-block::
-
-                  ./vllm_benchmark_report.sh \
-                      -s $test_option \
-                      -m {{model.model_repo}} \
-                      -g $num_gpu \
-                      -d {{model.precision}}
-
                .. note::
 
-                  For best performance, it's recommend to run with ``VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1``.
+                  For best performance, it's recommended to run with ``VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1``.
 
                   If you encounter the following error, pass your access-authorized Hugging
                   Face token to the gated models.
@@ -331,33 +331,33 @@ system's configuration.
 
             Here are some examples of running the benchmark with various options:
 
-            * Latency benchmark
-
-              Use this command to benchmark the latency of the {{model.model}} model on eight GPUs with :literal:`{{model.precision}}` precision.
-
-              .. code-block::
-
-                 ./vllm_benchmark_report.sh \
-                     -s latency \
-                     -m {{model.model_repo}} \
-                     -g 8 \
-                     -d {{model.precision}}
-
-              Find the latency report at ``./reports_{{model.precision}}_vllm_rocm{{unified_docker.rocm_version}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_latency_report.csv``.
-
             * Throughput benchmark
 
               Use this command to benchmark the throughput of the {{model.model}} model on eight GPUs with :literal:`{{model.precision}}` precision.
 
               .. code-block:: shell
 
-                 ./vllm_benchmark_report.sh \
-                     -s throughput \
-                     -m {{model.model_repo}} \
-                     -g 8 \
-                     -d {{model.precision}}
+                 export MAD_MODEL_NAME={{ model.mad_tag }}
+                 ./run.sh \
+                     --config configs/default.csv \
+                     --model_repo {{model.model_repo}} \
+                     --benchmark throughput
 
-              Find the throughput report at ``./reports_{{model.precision}}_vllm_rocm{{unified_docker.rocm_version}}/summary/{{model.model_repo.split('/', 1)[1] if '/' in model.model_repo else model.model_repo}}_throughput_report.csv``.
+              Find the throughput benchmark report at ``./{{ model.mad_tag }}_throughput.csv``.
+
+            * Serving benchmark
+
+              Use this command to benchmark the serving performance of the {{model.model}} model on eight GPUs with :literal:`{{model.precision}}` precision.
+
+              .. code-block::
+
+                 export MAD_MODEL_NAME={{ model.mad_tag }}
+                 ./run.sh \
+                     --config configs/default.csv \
+                     --model_repo {{model.model_repo}} \
+                     --benchmark serving
+
+              Find the serving benchmark report at ``./{{ model.mad_tag }}_serving.csv``.
 
             .. raw:: html
 
@@ -400,7 +400,7 @@ To reproduce this ROCm/vLLM Docker image release, follow these steps:
    .. code-block:: shell
 
       cd vllm
-      git checkout b432b7a285aa0dcb9677380936ffa74931bb6d6f
+      git checkout 340ea86dfe5955d6f9a9e767d6abab5aacf2c978
 
 3. Build the Docker image. Replace ``vllm-rocm`` with your desired image tag.
 
@@ -408,19 +408,16 @@ To reproduce this ROCm/vLLM Docker image release, follow these steps:
 
       docker build -f docker/Dockerfile.rocm -t vllm-rocm .
 
-Known issues and workarounds
-============================
-
-AITER does not support FP8 KV cache yet.
-
 Further reading
 ===============
 
 - To learn more about the options for latency and throughput benchmark scripts,
   see `<https://github.com/ROCm/vllm/tree/main/benchmarks>`_.
 
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
 - To learn more about system settings and management practices to configure your system for
-  MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
 
 - For application performance optimization strategies for HPC and AI workloads,
   including inference with vLLM, see :doc:`/how-to/rocm-for-ai/inference-optimization/workload`.

docs/how-to/rocm-for-ai/inference/index.rst

@@ -24,4 +24,6 @@ training, fine-tuning, and inference. It leverages popular machine learning fram
 
 - :doc:`PyTorch inference performance testing <benchmark-docker/pytorch-inference>`
 
+- :doc:`SGLang inference performance testing <benchmark-docker/sglang>`
+
 - :doc:`Deploying your model <deploy-your-model>`

docs/how-to/rocm-for-ai/install.rst

@@ -1,14 +1,14 @@
 .. meta::
-   :description: How to install ROCm and popular machine learning frameworks.
+   :description: How to install ROCm and popular deep learning frameworks.
    :keywords: ROCm, AI, LLM, train, fine-tune, FSDP, DeepSpeed, LLaMA, tutorial
 
 .. _rocm-for-ai-install:
 
-***********************************************
-Installing ROCm and machine learning frameworks
-***********************************************
+********************************************
+Installing ROCm and deep learning frameworks
+********************************************
 
-Before getting started, install ROCm and supported machine learning frameworks.
+Before getting started, install ROCm and supported deep learning frameworks.
 
 .. grid:: 1
 
@@ -24,12 +24,13 @@ If you’re new to ROCm, refer to the :doc:`ROCm quick start install guide for L
 If you’re using a Radeon GPU for graphics-accelerated applications, refer to the
 `Radeon installation instructions <https://rocm.docs.amd.com/projects/radeon/en/docs-6.1.3/docs/install/native_linux/install-radeon.html>`_.
 
-ROCm supports multiple :doc:`installation methods <rocm-install-on-linux:install/install-overview>`:
+You can install ROCm on :ref:`compatible systems <rocm-install-on-linux:reference/system-requirements>` via your Linux
+distribution's package manager. See the following documentation resources to get started:
+
+* :doc:`ROCm installation overview <rocm-install-on-linux:install/install-overview>`
 
 * :doc:`Using your Linux distribution's package manager <rocm-install-on-linux:install/install-methods/package-manager-index>`
 
-* :doc:`Using the AMDGPU installer <rocm-install-on-linux:install/install-methods/amdgpu-installer-index>`
-
 * :ref:`Multi-version installation <rocm-install-on-linux:installation-types>`
 
 .. grid:: 1
@@ -42,23 +43,16 @@ ROCm supports multiple :doc:`installation methods <rocm-install-on-linux:install
       If you encounter any issues during installation, refer to the
       :doc:`Installation troubleshooting <rocm-install-on-linux:reference/install-faq>` guide.
 
-Machine learning frameworks
-===========================
+Deep learning frameworks
+========================
 
-ROCm supports popular machine learning frameworks and libraries including `PyTorch
+ROCm supports deep learning frameworks and libraries including `PyTorch
 <https://pytorch.org/blog/pytorch-for-amd-rocm-platform-now-available-as-python-package>`_, `TensorFlow
-<https://tensorflow.org>`_, `JAX <https://jax.readthedocs.io/en/latest>`_, and `DeepSpeed
-<https://cloudblogs.microsoft.com/opensource/2022/03/21/supporting-efficient-large-model-training-on-amd-instinct-gpus-with-deepspeed/>`_.
+<https://tensorflow.org>`_, `JAX <https://jax.readthedocs.io/en/latest>`_, and more.
 
-Review the framework installation documentation. For ease-of-use, it's recommended to use official ROCm prebuilt Docker
+Review the :doc:`framework installation documentation <../deep-learning-rocm>`. For ease-of-use, it's recommended to use official ROCm prebuilt Docker
 images with the framework pre-installed.
 
-* :doc:`PyTorch for ROCm <rocm-install-on-linux:install/3rd-party/pytorch-install>`
-
-* :doc:`TensorFlow for ROCm <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
-
-* :doc:`JAX for ROCm <rocm-install-on-linux:install/3rd-party/jax-install>`
-
 Next steps
 ==========
 

docs/how-to/rocm-for-ai/training/benchmark-docker/megatron-lm.rst

@@ -1,3 +1,5 @@
+:orphan:
+
 .. meta::
    :description: How to train a model using Megatron-LM for ROCm.
    :keywords: ROCm, AI, LLM, train, Megatron-LM, megatron, Llama, tutorial, docker, torch
@@ -6,6 +8,14 @@
 Training a model with Megatron-LM for ROCm
 ******************************************
 
+.. caution::
+
+   The ROCm Megatron-LM framework now has limited support with this Docker
+   environment; it now focuses on Primus with Megatron-Core. See :doc:`primus-megatron`.
+
+   To learn how to migrate your existing workloads to Primus with Megatron-Core,
+   see :doc:`previous-versions/megatron-lm-primus-migration-guide`.
+
 The `Megatron-LM framework for ROCm <https://github.com/ROCm/Megatron-LM>`_ is
 a specialized fork of the robust Megatron-LM, designed to enable efficient
 training of large-scale language models on AMD GPUs. By leveraging AMD
@@ -20,13 +30,17 @@ essential components, including PyTorch, ROCm libraries, and Megatron-LM
 utilities. It contains the following software components to accelerate training
 workloads:
 
+.. note::
+
+   This Docker environment is based on Python 3.10 and Ubuntu 22.04. For an alternative environment with
+   Python 3.12 and Ubuntu 24.04, see the :doc:`previous ROCm Megatron-LM v25.6 Docker release <previous-versions/megatron-lm-v25.6>`.
+
 .. datatemplate:yaml:: /data/how-to/rocm-for-ai/training/megatron-lm-benchmark-models.yaml
 
    {% set dockers = data.dockers %}
-   {% if dockers|length > 1 %}
    .. tab-set::
 
-      {% for docker in data.dockers %}
+      {% for docker in dockers %}
       .. tab-item:: ``{{ docker.pull_tag }}``
          :sync: {{ docker.pull_tag }}
 
@@ -42,28 +56,14 @@ workloads:
 
             {% endfor %}
       {% endfor %}
-   {% elif dockers|length == 1 %}
-   .. list-table::
-      :header-rows: 1
-
-      * - Software component
-        - Version
-
-      {% for component_name, component_version in docker.components %}
-      * - {{ component_name }}
-        - {{ component_version }}
-
-      {% endfor %}
-   {% endif %}
 
    .. _amd-megatron-lm-model-support:
 
-   The following models are pre-optimized for performance on AMD Instinct MI300X series accelerators.
-
    Supported models
    ================
 
-   The following models are supported for training performance benchmarking with Megatron-LM and ROCm.
+   The following models are supported for training performance benchmarking with Megatron-LM and ROCm
+   on AMD Instinct MI300X series accelerators.
    Some instructions, commands, and training recommendations in this documentation might
    vary by model -- select one to get started.
 
@@ -177,7 +177,7 @@ Download the Docker image
       {% if dockers|length > 1 %}
       .. tab-set::
 
-         {% for docker in data.dockers %}
+         {% for docker in dockers %}
          .. tab-item:: {{ docker.doc_name }}
             :sync: {{ docker.pull_tag }}
 
@@ -227,10 +227,17 @@ Download the Docker image
       docker start megatron_training_env
       docker exec -it megatron_training_env bash
 
-The Docker container includes a pre-installed, verified version of the ROCm
-Megatron-LM development branch
-`<https://github.com/ROCm/Megatron-LM/tree/rocm_dev>`__, including necessary
-training scripts.
+4. **Megatron-LM backward compatibility setup** -- this Docker is primarily intended for use with Primus, but it maintains Megatron-LM compatibility with limited support.
+   To roll back to using Megatron-LM, follow these steps:
+
+   .. code-block:: shell
+
+      cd /workspace/Megatron-LM/
+      pip uninstall megatron-core
+      pip install -e .
+
+The Docker container hosts
+`<https://github.com/ROCm/Megatron-LM/tree/rocm_dev>`__ at verified commit ``e8e9edc``.
 
 .. _amd-megatron-lm-environment-setup:
 

docs/how-to/rocm-for-ai/training/benchmark-docker/mpt-llm-foundry.rst

@@ -73,7 +73,11 @@ document are not validated.
 
       .. code-block:: shell
 
-         python3 tools/run_models.py --tags pyt_mpt30b_training --keep-model-dir --live-output --clean-docker-cache
+         madengine run \
+             --tags pyt_mpt30b_training \
+             --keep-model-dir \
+             --live-output \
+             --clean-docker-cache
 
       .. tip::
 
@@ -90,7 +94,7 @@ document are not validated.
 
          For improved performance (training throughput), consider enabling TunableOp.
          By default, ``pyt_mpt30b_training`` runs with TunableOp disabled. To enable it,
-         run ``tools/run_models.py`` with the ``--tunableop on`` argument or edit the
+         run ``madengine run`` with the ``--tunableop on`` argument or edit the
          ``models.json`` configuration before running training.
 
          Although this might increase the initial training time, it can result in a performance gain.
@@ -172,4 +176,13 @@ Key performance metrics include:
 
     Overall training loss. A decreasing trend indicates the model is learning effectively.
 
+Further reading
+===============
 
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
+- To learn more about system settings and management practices to configure your system for
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
+
+- For a list of other ready-made Docker images for AI with ROCm, see
+  `AMD Infinity Hub <https://www.amd.com/en/developer/resources/infinity-hub.html#f-amd_hub_category=AI%20%26%20ML%20Models>`_.

docs/how-to/rocm-for-ai/training/benchmark-docker/previous-versions/megatron-lm-history.rst

@@ -16,12 +16,20 @@ previous releases of the ``ROCm/megatron-lm`` Docker image on `Docker Hub <https
      - Components
      - Resources
 
-   * - v25.6 (latest)
+   * - v25.7 (latest)
+     - 
+       * ROCm 
+       * PyTorch 
+     - 
+       * :doc:`Documentation <../megatron-lm>`
+       * `Docker Hub (py310) <https://hub.docker.com/layers/rocm/megatron-lm/v25.7_py310/images/sha256-6189df849feeeee3ae31bb1e97aef5006d69d2b90c134e97708c19632e20ab5a>`__
+
+   * - v25.6
      - 
        * ROCm 6.4.1
        * PyTorch 2.8.0a0+git7d205b2
      - 
-       * :doc:`Documentation <../megatron-lm>`
+       * :doc:`Documentation <megatron-lm-v25.6>`
        * `Docker Hub (py312) <https://hub.docker.com/layers/rocm/megatron-lm/v25.6_py312/images/sha256-482ff906532285bceabdf2bda629bd32cb6174d2d07f4243a736378001b28df0>`__
        * `Docker Hub (py310) <https://hub.docker.com/layers/rocm/megatron-lm/v25.6_py310/images/sha256-9627bd9378684fe26cb1a10c7dd817868f553b33402e49b058355b0f095568d6>`__
 

docs/how-to/rocm-for-ai/training/benchmark-docker/previous-versions/megatron-lm-primus-migration-guide.rst

@@ -0,0 +1,175 @@
+:orphan:
+
+**********************************************************************
+Migrating workloads to Primus (Megatron-Core backend) from Megatron-LM
+**********************************************************************
+
+Primus supports Megatron-Core as backend optimization library,
+replacing ROCm Megatron-LM. This document outlines the steps to migrate
+workload from ROCm Megatron-LM to Primus with the Megatron-Core backend.
+
+Model architecture
+==================
+
+ROCm Megatron-LM defines model architecture parameters in the training scripts;
+for example, the Llama 3 8B model parameters are defined in
+`examples/llama/train_llama3.sh <https://github.com/ROCm/Megatron-LM/blob/rocm_dev/examples/llama/train_llama3.sh#L117>`__
+as shown below:
+
+.. code-block:: bash
+
+   HIDDEN_SIZE=4096 
+   FFN_HIDDEN_SIZE=14336 
+   NUM_LAYERS=32 
+   NUM_HEADS=32 
+   NUM_KV_HEADS=8
+
+Primus defines the model architecture through model YAML configuration files
+inside the ``primus/configs/models/megatron/`` repository. For example, Llama 3 8B
+model architecture parameters are defined in
+`primus/configs/models/megatron/llama3_8B.yaml <https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/primus/configs/models/megatron/llama3_8B.yaml>`__
+as shown below:
+
+.. code-block:: yaml
+
+   bases:
+     - llama3_base.yaml
+
+   tokenizer_type: Llama3Tokenizer
+   tokenizer_model: meta-llama/Llama-3.1-8B
+
+   ffn_hidden_size: 14336
+   hidden_size: 4096
+   num_attention_heads: 32
+   num_layers: 32
+   num_query_groups: 8
+
+Primus' model config files follow a hierarchical design, meaning that new model
+config YAMLs can inherit existing model config files by importing them as
+bases. For example,
+`llama3.1_8B.yaml <https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/primus/configs/models/megatron/llama3.1_8B.yaml>`__
+uses ``llama3_8B.yaml`` as a base config and overrides few parameters, as shown below.
+In this example, ``llama3.1_8B`` overrides the ``max_position_embeddings`` value:
+
+.. code-block:: yaml
+
+   bases:
+     - llama3_8B.yaml
+
+   tokenizer_type: Llama3Tokenizer
+   tokenizer_model: meta-llama/Llama-3.1-8B
+
+   max_position_embeddings: 131072
+
+.. tip::
+
+   Primus provides ``llama_base.yaml`` as the base configuration, which can be
+   used as bases for additional model architectures. For example,
+   `mixtral_base.yaml <https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/primus/configs/models/megatron/mixtral_base.yaml>`__
+   and
+   `deepseek_v3_base.yaml <https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/primus/configs/models/megatron/deepseek_v3_base.yaml>`__
+   define ``llama_base.yaml`` as its base.
+
+   .. code-block:: yaml
+
+      # Example mixtral_base.yaml:
+
+      bases:
+        - llama_base.yaml
+
+      init_method_std: 0.01
+      rotary_base: 1000000
+      qk_layernorm: false
+
+      group_query_attention: true
+      num_query_groups: 8
+
+      # moe parameters
+      num_experts: 8
+      moe_router_topk: 2
+      moe_router_load_balancing_type: aux_loss
+      moe_aux_loss_coeff: 1e-2
+      moe_grouped_gemm: true
+      moe_token_dispatcher_type: alltoall
+
+It is recommended to add a new ``${MODEL_NAME}_base.yaml`` to add a new
+category of model and define new models on top of it. For example, to add
+Qwen2.5 models in Primus, we define
+`qwen2.5_base.yaml <https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/primus/configs/models/megatron/qwen2.5_base.yaml>`__
+and build
+`qwen2.5_7B.yaml <https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/primus/configs/models/megatron/qwen2.5_7B.yaml>`__
+and
+`qwen2.5_72B.yaml <https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/primus/configs/models/megatron/qwen2.5_72B.yaml>`__
+using ``qwen2.5_base.yaml`` as the base config.
+
+Training parameters
+===================
+
+ROCm Megatron-LM also defines the training parameters, like batch size,
+tensor-parallelism, precision, as so on, in the training scripts. For example,
+Llama3 8B model parameters are defined in
+`examples/llama/train_llama3.sh <https://github.com/ROCm/Megatron-LM/blob/rocm_dev/examples/llama/train_llama3.sh>`__
+as shown below:
+
+.. code-block:: bash
+
+   TP="${TP:-8}"
+   PP="${PP:-1}"
+   CP="${CP:-1}"
+   MBS="${MBS:-1}"
+   BS="${BS:-8}"
+
+Primus defines the training parameters in top-level YAML files -- see
+`examples/megatron/configs/
+<https://github.com/AMD-AIG-AIMA/Primus/tree/v0.1.0-rc1/examples/megatron/configs>`__.
+For example, the `llama3.1_8B-pretrain.yaml
+<https://github.com/AMD-AIG-AIMA/Primus/blob/v0.1.0-rc1/examples/megatron/configs/llama3.1_8B-pretrain.yaml>`__
+configuration imports the ``llama3.1_8B.yaml`` model architecture file. Users can then override
+the default training parameters in ``llama3.1_8B-pretrain.yaml``.
+
+.. code-block:: yaml
+
+   # model to run
+   model: llama3.1_8B.yaml  # Model architecture yaml
+   overrides:
+     # log
+     # disable_wandb: false
+     # disable_tensorboard: false
+     stderr_sink_level: DEBUG
+
+     log_avg_skip_iterations: 2
+     log_avg_reset_interval: 50
+
+     train_iters: 50
+     micro_batch_size: 2
+     global_batch_size: 128
+
+     seq_length: 8192
+     max_position_embeddings: 8192
+
+     lr: 1.0e-5
+     min_lr: 0.0
+     lr_warmup_iters: 2
+     lr_decay_iters: null
+     lr_decay_style: cosine
+     weight_decay: 0.1
+     adam_beta1: 0.9
+     adam_beta2: 0.95
+     eod_mask_loss: true
+     init_method_std: 0.008
+     norm_epsilon: 1.0e-6
+
+Backward compatibility with Megatron-LM
+=======================================
+
+The Dockerized environment used for Primus maintains compatibility with Megatron-LM with
+limited support. To roll back to using Megatron-LM, follow these steps.
+
+.. code-block:: shell
+
+   cd /workspace/Megatron-LM/
+   pip uninstall megatron-core
+   pip install -e .
+
+Once Megatron-LM is installed, follow :doc:`the documentation <../megatron-lm>` to run workloads as
+usual.

docs/how-to/rocm-for-ai/training/benchmark-docker/primus-megatron.rst

@@ -0,0 +1,602 @@
+.. meta::
+   :description: How to train a model using Megatron-LM for ROCm.
+   :keywords: ROCm, AI, LLM, train, Megatron-LM, megatron, Llama, tutorial, docker, torch
+
+**********************************************
+Training a model with Primus and Megatron-Core
+**********************************************
+
+`Primus <https://github.com/AMD-AIG-AIMA/Primus>`__ is a unified and flexible
+LLM training framework designed to streamline training. It streamlines LLM
+training on AMD Instinct accelerators using a modular, reproducible configuration paradigm.
+Primus is backend-agnostic and supports multiple training engines -- including Megatron-Core.
+
+.. note::
+
+   Primus with the Megatron-Core backend is intended to replace ROCm
+   Megatron-LM in this Dockerized training environment. To learn how to migrate
+   workloads from Megatron-LM to Primus with Megatron-Core, see
+   :doc:`previous-versions/megatron-lm-primus-migration-guide`.
+
+For ease of use, AMD provides a ready-to-use Docker image for MI300 series accelerators
+containing essential components for Primus and Megatron-Core.
+
+.. note::
+
+   This Docker environment is based on Python 3.10 and Ubuntu 22.04. For an alternative environment with
+   Python 3.12 and Ubuntu 24.04, see the :doc:`previous ROCm Megatron-LM v25.6 Docker release <previous-versions/megatron-lm-v25.6>`.
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/training/primus-megatron-benchmark-models.yaml
+
+   {% set dockers = data.dockers %}
+   {% set docker = dockers[0] %}
+   .. list-table::
+      :header-rows: 1
+
+      * - Software component
+        - Version
+
+      {% for component_name, component_version in docker.components.items() %}
+      * - {{ component_name }}
+        - {{ component_version }}
+      {% endfor %}
+
+.. _amd-primus-megatron-lm-model-support:
+
+Supported models
+================
+
+The following models are pre-optimized for performance on AMD Instinct MI300X series accelerators.
+Some instructions, commands, and training examples in this documentation might
+vary by model -- select one to get started.
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/training/primus-megatron-benchmark-models.yaml
+
+   {% set model_groups = data.model_groups %}
+   .. raw:: html
+
+         <div id="vllm-benchmark-ud-params-picker" class="container-fluid">
+           <div class="row">
+             <div class="col-2 me-2 model-param-head">Model</div>
+             <div class="row col-10">
+      {% for model_group in model_groups %}
+               <div class="col-3 model-param" data-param-k="model-group" data-param-v="{{ model_group.tag }}" tabindex="0">{{ model_group.group }}</div>
+      {% endfor %}
+             </div>
+           </div>
+
+           <div class="row mt-1">
+             <div class="col-2 me-2 model-param-head">Model variant</div>
+             <div class="row col-10">
+      {% for model_group in model_groups %}
+         {% set models = model_group.models %}
+         {% for model in models %}
+            {% if models|length % 3 == 0 %}
+               <div class="col-4 model-param" data-param-k="model" data-param-v="{{ model.mad_tag }}" data-param-group="{{ model_group.tag }}" tabindex="0">{{ model.model }}</div>
+            {% else %}
+               <div class="col-6 model-param" data-param-k="model" data-param-v="{{ model.mad_tag }}" data-param-group="{{ model_group.tag }}" tabindex="0">{{ model.model }}</div>
+            {% endif %}
+         {% endfor %}
+      {% endfor %}
+             </div>
+           </div>
+         </div>
+
+.. note::
+
+   Some models, such as Llama, require an external license agreement through
+   a third party (for example, Meta).
+
+System validation
+=================
+
+Before running AI workloads, it's important to validate that your AMD hardware is configured
+correctly and performing optimally.
+
+If you have already validated your system settings, including aspects like NUMA auto-balancing, you
+can skip this step. Otherwise, complete the procedures in the :ref:`System validation and
+optimization <rocm-for-ai-system-optimization>` guide to properly configure your system settings
+before starting training.
+
+To test for optimal performance, consult the recommended :ref:`System health benchmarks
+<rocm-for-ai-system-health-bench>`. This suite of tests will help you verify and fine-tune your
+system's configuration.
+
+.. _mi300x-amd-primus-megatron-lm-training:
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/training/primus-megatron-benchmark-models.yaml
+
+   {% set dockers = data.dockers %}
+      {% set docker = dockers[0] %}
+
+   Environment setup
+   =================
+
+   Use the following instructions to set up the environment, configure the script to train models, and
+   reproduce the benchmark results on MI300X series accelerators with the ``{{ docker.pull_tag }}`` image.
+
+   .. _amd-primus-megatron-lm-requirements:
+
+   Download the Docker image
+   -------------------------
+
+   1. Use the following command to pull the Docker image from Docker Hub.
+
+      .. code-block:: shell
+
+         docker pull {{ docker.pull_tag }}
+
+   2. Launch the Docker container.
+
+      .. code-block:: shell
+
+         docker run -it \
+             --device /dev/dri \
+             --device /dev/kfd \
+             --device /dev/infiniband \
+             --network host --ipc host \
+             --group-add video \
+             --cap-add SYS_PTRACE \
+             --security-opt seccomp=unconfined \
+             --privileged \
+             -v $HOME:$HOME \
+             --shm-size 128G \
+             --name primus_training_env \
+             {{ docker.pull_tag }}
+
+3. Use these commands if you exit the ``primus_training_env`` container and need to return to it.
+
+   .. code-block:: shell
+
+      docker start primus_training_env
+      docker exec -it primus_training_env bash
+
+The Docker container hosts verified release tag ``v0.1.0-rc1`` of the `Primus
+<https://github.com/AMD-AIG-AIMA/Primus/tree/v0.1.0-rc1>`__ repository.
+
+.. _amd-primus-megatron-lm-environment-setup:
+
+Configuration
+=============
+
+Primus defines a training configuration in YAML for each model in
+`examples/megatron/configs <https://github.com/AMD-AIG-AIMA/Primus/tree/v0.1.0-rc1/examples/megatron/configs>`__.
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/training/primus-megatron-benchmark-models.yaml
+
+   {% set model_groups = data.model_groups %}
+   {% for model_group in model_groups %}
+      {% for model in model_group.models %}
+   .. container:: model-doc {{ model.mad_tag }}
+
+      To update training parameters for {{ model.model }}, you can update ``examples/megatron/configs/{{ model.config_name }}``.
+      Note that training configuration YAML files for other models follow this naming convention.
+
+      {% endfor %}
+   {% endfor %}
+
+.. note::
+
+   See :ref:`Key options <amd-primus-megatron-lm-benchmark-test-vars>` for more information on configuration options.
+
+Dataset options
+---------------
+
+You can use either mock data or real data for training.
+
+* Mock data can be useful for testing and validation. Use the ``mock_data`` field to toggle between mock and real data. The default
+  value is ``true`` for enabled.
+
+  .. code-block:: yaml
+
+     mock_data: true
+
+* If you're using a real dataset, update the ``train_data_path`` field to point to the location of your dataset.
+
+  .. code-block:: bash
+
+     mock_data: false
+     train_data_path: /path/to/your/dataset
+
+  Ensure that the files are accessible inside the Docker container.
+
+.. _amd-primus-megatron-lm-tokenizer:
+
+Tokenizer
+---------
+
+In Primus, each model uses a tokenizer from Hugging Face. For example, Llama
+3.1 8B model uses ``tokenizer_model: meta-llama/Llama-3.1-8B`` and
+``tokenizer_type: Llama3Tokenizer`` defined in the `llama3.1-8B model
+<https://github.com/AMD-AIG-AIMA/Primus/tree/v0.1.0-rc1/primus/configs/models/megatron/llama3.1_8B.yaml>`__
+definition. As such, you need to set the ``HF_TOKEN`` environment variable with
+right permissions to access the tokenizer for each model.
+
+.. code-block:: bash
+
+   # Export your HF_TOKEN in the workspace
+   export HF_TOKEN=<your_hftoken>
+
+.. _amd-primus-megatron-lm-run-training:
+
+Run training
+============
+
+Use the following example commands to set up the environment, configure
+:ref:`key options <amd-primus-megatron-lm-benchmark-test-vars>`, and run training on
+MI300X series accelerators with the AMD Megatron-LM environment.
+
+Single node training
+--------------------
+
+To run training on a single node, navigate to ``/workspace/Primus`` and use the following setup command:
+
+.. code-block:: shell
+
+   pip install -r requirements.txt
+   export HSA_NO_SCRATCH_RECLAIM=1
+   export NVTE_CK_USES_BWD_V3=1
+
+Once setup is complete, run the appropriate training command.
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-3.3-70b
+
+   To run pre-training for Llama 3.3 70B BF16, run:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama3.3_70B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh \
+          --micro_batch_size 2 \
+          --global_batch_size 16 \
+          --train_iters 50
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-3.1-8b
+
+   To run pre-training for Llama 3.1 8B FP8, run:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama3.1_8B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh \
+          --train_iters 50 \
+          --fp8 hybrid
+
+   For Llama 3.1 8B BF16, use the following command:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama3.1_8B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh --train_iters 50
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-3.1-70b
+
+   To run pre-training for Llama 3.1 70B BF16, run:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama3.1_70B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh \
+           --train_iters 50
+
+   To run the training on a single node for Llama 3.1 70B FP8 with proxy, use the following command:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama3.1_70B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh \
+          --train_iters 50 \
+          --num_layers 40 \
+          --fp8 hybrid \
+          --no_fp8_weight_transpose_cache true
+
+   .. note::
+
+      Use two or more nodes to run the *full* Llama 70B model with FP8 precision.
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-2-7b
+
+   To run pre-training for Llama 2 7B FP8, run:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama2_7B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh \
+          --train_iters 50 \
+          --fp8 hybrid
+
+   To run pre-training for Llama 2 7B BF16, run:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama2_7B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh --train_iters 50
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-2-70b
+
+   To run pre-training for Llama 2 70B BF16, run:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/llama2_70B-pretrain.yaml \
+      bash ./examples/run_pretrain.sh --train_iters 50 
+
+.. container:: model-doc primus_pyt_megatron_lm_train_deepseek-v3-proxy
+
+   To run training on a single node for DeepSeek-V3 (MoE with expert parallel) with 3-layer proxy, 
+   use the following command:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/deepseek_v3-pretrain.yaml \
+      bash examples/run_pretrain.sh \
+          --num_layers 3 \
+          --moe_layer_freq 1 \
+          --train_iters 50
+
+.. container:: model-doc primus_pyt_megatron_lm_train_deepseek-v2-lite-16b
+
+   To run training on a single node for DeepSeek-V2-Lite (MoE with expert parallel),
+   use the following command:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/deepseek_v2_lite-pretrain.yaml \
+      bash examples/run_pretrain.sh \
+          --global_batch_size 256 \
+          --train_iters 50
+
+.. container:: model-doc primus_pyt_megatron_lm_train_mixtral-8x7b
+
+   To run training on a single node for Mixtral 8x7B (MoE with expert parallel),
+   use the following command:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/mixtral_8x7B_v0.1-pretrain.yaml \
+      bash examples/run_pretrain.sh --train_iters 50
+
+.. container:: model-doc primus_pyt_megatron_lm_train_mixtral-8x22b-proxy
+
+   To run training on a single node for Mixtral 8x7B (MoE with expert parallel) with 4-layer proxy,
+   use the following command:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/mixtral_8x22B_v0.1-pretrain.yaml \
+      bash examples/run_pretrain.sh \
+          --num_layers 4 \
+          --pipeline_model_parallel_size 1 \
+          --micro_batch_size 1 \
+          --global_batch_size 16 \
+          --train_iters 50
+
+.. container:: model-doc primus_pyt_megatron_lm_train_qwen2.5-7b
+
+   To run training on a single node for Qwen 2.5 7B BF16, use the following
+   command:
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/qwen2.5_7B-pretrain.yaml \
+      bash examples/run_pretrain.sh --train_iters 50
+
+   For FP8, use the following command.
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/qwen2.5_7B-pretrain.yaml \
+      bash examples/run_pretrain.sh \
+          --train_iters 50 \
+          --fp8 hybrid
+
+.. container:: model-doc primus_pyt_megatron_lm_train_qwen2.5-72b
+
+   To run the training on a single node for Qwen 2.5 72B BF16, use the following command.
+
+   .. code-block:: shell
+
+      EXP=examples/megatron/configs/qwen2.5_72B-pretrain.yaml \
+      bash examples/run_pretrain.sh --train_iters 50
+
+Multi-node training examples
+----------------------------
+
+To run training on multiple nodes, you can use the
+`run_slurm_pretrain.sh <https://github.com/AMD-AIG-AIMA/Primus/tree/v0.1.0-rc1/examples/run_slurm_pretrain.sh>`__
+to launch the multi-node workload. Use the following steps to setup your environment:
+
+.. datatemplate:yaml:: /data/how-to/rocm-for-ai/training/primus-megatron-benchmark-models.yaml
+
+   {% set dockers = data.dockers %}
+   {% set docker = dockers[0] %}
+
+   .. code-block:: shell
+
+      cd /workspace/Primus/
+      export DOCKER_IMAGE={{ docker.pull_tag }}
+      export HF_TOKEN=<your_HF_token>
+      export HSA_NO_SCRATCH_RECLAIM=1
+      export NVTE_CK_USES_BWD_V3=1
+      export NCCL_IB_HCA=<your_NCCL_IB_HCA> # specify which RDMA interfaces to use for communication
+      export NCCL_SOCKET_IFNAME=<your_NCCL_SOCKET_IFNAME> # your Network Interface
+      export GLOO_SOCKET_IFNAME=<your_GLOO_SOCKET_IFNAME> # your Network Interface
+      export NCCL_IB_GID_INDEX=3 # Set InfiniBand GID index for NCCL communication. Default is 3 for ROCE
+
+.. note::
+
+   * Make sure correct network drivers are installed on the nodes. If inside a Docker, either install the drivers inside the Docker container or pass the network drivers from the host while creating Docker container.
+   * If ``NCCL_IB_HCA`` and ``NCCL_SOCKET_IFNAME`` are not set, Primus will try to auto-detect. However, since NICs can vary accross different cluster, it is encouraged to explicitly export your NCCL parameters for the cluster.
+   * To find your network interface, you can use ``ip a``.
+   * To find RDMA interfaces, you can use ``ibv_devices`` to get the list of all the RDMA/IB  devices.
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-3.3-70b
+
+   To train Llama 3.3 70B FP8 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/llama3.3_70B-pretrain.yaml \
+      bash examples/run_slurm_pretrain.sh \
+          --micro_batch_size 4 \
+          --global_batch_size 256 \
+          --recompute_num_layers 80 \
+          --no_fp8_weight_transpose_cache true \
+          --fp8 hybrid
+
+   To train Llama 3.3 70B BF16 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/llama3.3_70B-pretrain.yaml \
+      bash examples/run_slurm_pretrain.sh \
+          --micro_batch_size 1 \
+          --global_batch_size 256 \
+          --recompute_num_layers 12
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-3.1-8b
+
+   To train Llama 3.1 8B FP8 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      # Adjust the training parameters. For e.g., `global_batch_size: 8 * #single_node_bs` for 8 nodes in this case 
+      NNODES=8 EXP=examples/megatron/configs/llama3.1_8B-pretrain.yaml \
+      bash ./examples/run_slurm_pretrain.sh \
+          --global_batch_size 1024 \
+          --fp8 hybrid
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-3.1-70b
+
+   To train Llama 3.1 70B FP8 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/llama3.1_70B-pretrain.yaml \
+      bash examples/run_slurm_pretrain.sh \
+          --micro_batch_size 4 \
+          --global_batch_size 256 \
+          --recompute_num_layers 80 \
+          --no_fp8_weight_transpose_cache true \
+          --fp8 hybrid
+
+   To train Llama 3.1 70B BF16 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/llama3.1_70B-pretrain.yaml \
+      bash examples/run_slurm_pretrain.sh \
+          --micro_batch_size 1 \
+          --global_batch_size 256 \
+          --recompute_num_layers 12
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-2-7b
+
+   To train Llama 2 8B FP8 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      # Adjust the training parameters. For e.g., `global_batch_size: 8 * #single_node_bs` for 8 nodes in this case 
+      NNODES=8 EXP=examples/megatron/configs/llama2_7B-pretrain.yaml bash ./examples/run_slurm_pretrain.sh --global_batch_size 2048 --fp8 hybrid
+
+.. container:: model-doc primus_pyt_megatron_lm_train_llama-2-70b
+
+   To train Llama 2 70B FP8 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/llama2_70B-pretrain.yaml \
+      bash examples/run_slurm_pretrain.sh \
+          --micro_batch_size 10 \
+          --global_batch_size 640 \
+          --recompute_num_layers 80 \
+          --no_fp8_weight_transpose_cache true \
+          --fp8 hybrid
+
+   To train Llama 2 70B BF16 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/llama2_70B-pretrain.yaml \
+      bash ./examples/run_slurm_pretrain.sh \
+          --micro_batch_size 2 \
+          --global_batch_size 1536 \
+          --recompute_num_layers 12
+
+.. container:: model-doc primus_pyt_megatron_lm_train_mixtral-8x7b
+
+   To train Mixtral 8x7B BF16 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/mixtral_8x7B_v0.1-pretrain.yaml \
+      bash examples/run_slurm_pretrain.sh \
+          --micro_batch_size 2 \
+          --global_batch_size 256
+
+.. container:: model-doc primus_pyt_megatron_lm_train_qwen2.5-72b
+
+   To train Qwen2.5 72B FP8 on 8 nodes, run:
+
+   .. code-block:: shell
+
+      NNODES=8 EXP=examples/megatron/configs/qwen2.5_72B-pretrain.yaml \
+      bash examples/run_slurm_pretrain.sh \
+          --micro_batch_size 8 \
+          --global_batch_size 512 \
+          --recompute_num_layers 80 \
+          --no_fp8_weight_transpose_cache true \
+          --fp8 hybrid
+
+.. _amd-primus-megatron-lm-benchmark-test-vars:
+
+Key options
+-----------
+
+The following are key options to take note of
+
+fp8
+  ``hybrid`` enables FP8 GEMMs.
+
+use_torch_fsdp2
+  ``use_torch_fsdp2: 1``  enables torch fsdp-v2. If FSDP is enabled,
+  set ``use_distributed_optimizer`` and ``overlap_param_gather`` to ``false``.
+
+profile
+  To enable PyTorch profiling, set these parameters:
+
+  .. code-block:: yaml
+
+     profile: true
+     use_pytorch_profiler: true
+     profile_step_end: 7
+     profile_step_start: 6
+
+train_iters
+  The total number of iterations (default: 50).
+
+mock_data
+  True by default.
+
+micro_batch_size
+  Micro batch size.
+
+global_batch_size
+  Global batch size.
+
+recompute_granularity
+  For activation checkpointing.
+
+num_layers
+  For using a reduced number of layers as with proxy models.
+
+Previous versions
+=================
+
+See :doc:`previous-versions/megatron-lm-history` to find documentation for previous releases
+of the ``ROCm/megatron-lm`` Docker image.
+
+This training environment now uses Primus with Megatron as the primary
+configuration. Limited support for the legacy ROCm Megatron-LM is still
+available. For instructions on using ROCm Megatron-LM, see the
+:doc:`megatron-lm` document.

docs/how-to/rocm-for-ai/training/benchmark-docker/pytorch-training.rst

@@ -142,7 +142,11 @@ The following models are pre-optimized for performance on the AMD Instinct MI325
             .. code-block:: shell
 
                export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
-               python3 tools/run_models.py --tags {{ model.mad_tag }} --keep-model-dir --live-output --timeout 28800
+               madengine run \
+                   --tags {{ model.mad_tag }} \
+                   --keep-model-dir \
+                   --live-output \
+                   --timeout 28800
 
             MAD launches a Docker container with the name
             ``container_ci-{{ model.mad_tag }}``, for example. The latency and throughput reports of the
@@ -427,6 +431,17 @@ The following models are pre-optimized for performance on the AMD Instinct MI325
 
                For examples of benchmarking commands, see `<https://github.com/ROCm/MAD/tree/develop/benchmark/pytorch_train#benchmarking-examples>`__.
 
+Further reading
+===============
+
+- To learn more about MAD and the ``madengine`` CLI, see the `MAD usage guide <https://github.com/ROCm/MAD?tab=readme-ov-file#usage-guide>`__.
+
+- To learn more about system settings and management practices to configure your system for
+  AMD Instinct MI300X series accelerators, see `AMD Instinct MI300X system optimization <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html>`_.
+
+- For a list of other ready-made Docker images for AI with ROCm, see
+  `AMD Infinity Hub <https://www.amd.com/en/developer/resources/infinity-hub.html#f-amd_hub_category=AI%20%26%20ML%20Models>`_.
+
 Previous versions
 =================
 

docs/how-to/rocm-for-ai/training/index.rst

@@ -21,6 +21,8 @@ In this guide, you'll learn about:
 
 - Training a model
 
+  - :doc:`With Primus (Megatron-LM backend) <benchmark-docker/primus-megatron>`
+
   - :doc:`With Megatron-LM <benchmark-docker/megatron-lm>`
 
   - :doc:`With PyTorch <benchmark-docker/pytorch-training>`

docs/reference/gpu-arch-specs.rst

@@ -285,7 +285,7 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
           - Radeon AI PRO R9700
           - RDNA4
           - gfx1201
-          - 16
+          - 32
           - 64
           - 32 or 64
           - 128

docs/reference/precision-support.rst

@@ -55,7 +55,7 @@ The floating-point types supported by ROCm are listed in the following table.
 
 .. list-table::
     :header-rows: 1
-    :widths: 15,15,70
+    :widths: 15,25,60
 
     *
       - Type name
@@ -63,18 +63,19 @@ The floating-point types supported by ROCm are listed in the following table.
       - Description
     *
       - float8 (E4M3)
-      - ``__hip_fp8_e4m3_fnuz``
-      - An 8-bit floating-point number that mostly follows IEEE-754 conventions
-        and **S1E4M3** bit layout, as described in `8-bit Numerical Formats for Deep Neural Networks <https://arxiv.org/abs/2206.02915>`_,
-        with expanded range and no infinity or signed zero. NaN is represented
-        as negative zero.
+      - | ``__hip_fp8_e4m3_fnuz``,
+        | ``__hip_fp8_e4m3``
+      - An 8-bit floating-point number with **S1E4M3** bit layout, as described in :doc:`low precision floating point types page <hip:reference/low_fp_types>`.
+        The FNUZ variant has expanded range with no infinity or signed zero (NaN represented as negative zero),
+        while the OCP variant follows the Open Compute Project specification.
     *
       - float8 (E5M2)
-      - ``__hip_fp8_e5m2_fnuz``
-      - An 8-bit floating-point number mostly following IEEE-754 conventions and
-        **S1E5M2** bit layout, as described in `8-bit Numerical Formats for Deep Neural Networks <https://arxiv.org/abs/2206.02915>`_,
-        with expanded range and no infinity or signed zero. NaN is represented
-        as negative zero.
+      - | ``__hip_fp8_e5m2_fnuz``,
+        | ``__hip_fp8_e5m2``
+      - An 8-bit floating-point number with **S1E5M2** bit layout, as described in :doc:`low precision floating point types page <hip:reference/low_fp_types>`.
+        The FNUZ variant has expanded range with no infinity or signed zero (NaN represented as negative zero),
+        while the OCP variant follows the Open Compute Project specification.
+
     *
       - float16
       - ``half``
@@ -107,9 +108,8 @@ The floating-point types supported by ROCm are listed in the following table.
   * The float8 and tensorfloat32 types are internal types used in calculations
     in Matrix Cores and can be stored in any type of the same size.
 
-  * The encodings for FP8 (E5M2) and FP8 (E4M3) that the
-    MI300 series natively supports differ from the FP8 (E5M2) and FP8 (E4M3)
-    encodings used in NVIDIA H100
+  * CNDA3 natively supports FP8 FNUZ (E4M3 and E5M2), which differs from the customised
+    FP8 format used in NVIDIA's H100
     (`FP8 Formats for Deep Learning <https://arxiv.org/abs/2209.05433>`_).
 
   * In some AMD documents and articles, float8 (E5M2) is referred to as bfloat8.
@@ -128,7 +128,7 @@ pages.
     :header-rows: 1
 
     *
-      -  Icon
+      - Icon
       - Definition
 
     *
@@ -163,12 +163,137 @@ pages.
   * Any type can be emulated by software, but this page does not cover such
     cases.
 
-Data type support by Hardware Architecture
+Data type support by hardware architecture
 ==========================================
 
-The MI200 series GPUs, which include MI210, MI250, and MI250X, are based on the
-CDNA2 architecture. The MI300 series GPUs, consisting of MI300A, MI300X, and
-MI325X, are based on the CDNA3 architecture.
+AMD's GPU lineup spans multiple architecture generations:
+
+* CDNA1 architecture: includes models such as MI100
+* CDNA2 architecture: includes models such as MI210, MI250, and MI250X
+* CDNA3 architecture: includes models such as MI300A, MI300X, and MI325X
+* RDNA3 architecture: includes models such as RX 7900XT and RX 7900XTX
+* RDNA4 architecture: includes models such as RX 9070 and RX 9070XT
+
+HIP C++ type implementation support
+-----------------------------------
+
+The HIP C++ types available on different hardware platforms are listed in the
+following table.
+
+.. list-table::
+    :header-rows: 1
+
+    *
+      - HIP C++ Type
+      - CDNA1
+      - CDNA2
+      - CDNA3
+      - RDNA3
+      - RDNA4
+
+    *
+      - ``int8_t``, ``uint8_t``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+    *
+      - ``int16_t``, ``uint16_t``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+    *
+      - ``int32_t``, ``uint32_t``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+    *
+      - ``int64_t``, ``uint64_t``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+    *
+      - ``__hip_fp8_e4m3_fnuz``
+      - ❌
+      - ❌
+      - ✅
+      - ❌
+      - ❌
+
+    *
+      - ``__hip_fp8_e5m2_fnuz``
+      - ❌
+      - ❌
+      - ✅
+      - ❌
+      - ❌
+
+    *
+      - ``__hip_fp8_e4m3``
+      - ❌
+      - ❌
+      - ❌
+      - ❌
+      - ✅
+
+    *
+      - ``__hip_fp8_e5m2``
+      - ❌
+      - ❌
+      - ❌
+      - ❌
+      - ✅
+
+    *
+      - ``half``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+    *
+      - ``bfloat16``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+    *
+      - ``float``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+    *
+      - ``double``
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+      - ✅
+
+.. note::
+
+  Library support for specific data types is contingent upon hardware support.
+  Even if a ROCm library indicates support for a particular data type, that type
+  will only be fully functional if the underlying hardware architecture (as shown
+  in the table above) also supports it. For example, fp8 types are only available
+  on architectures shown with a checkmark in the relevant rows.
 
 Compute units support
 ---------------------
@@ -190,19 +315,33 @@ The following table lists data type support for compute units.
         - int32
         - int64
       *
-        - MI100
+        - CDNA1
         - ✅
         - ✅
         - ✅
         - ✅
       *
-        - MI200 series
+        - CDNA2
         - ✅
         - ✅
         - ✅
         - ✅
       *
-        - MI300 series
+        - CDNA3
+        - ✅
+        - ✅
+        - ✅
+        - ✅
+
+      *
+        - RDNA3
+        - ✅
+        - ✅
+        - ✅
+        - ✅
+
+      *
+        - RDNA4
         - ✅
         - ✅
         - ✅
@@ -224,7 +363,7 @@ The following table lists data type support for compute units.
         - float32
         - float64
       *
-        - MI100
+        - CDNA1
         - ❌
         - ❌
         - ✅
@@ -233,7 +372,7 @@ The following table lists data type support for compute units.
         - ✅
         - ✅
       *
-        - MI200 series
+        - CDNA2
         - ❌
         - ❌
         - ✅
@@ -242,7 +381,27 @@ The following table lists data type support for compute units.
         - ✅
         - ✅
       *
-        - MI300 series
+        - CDNA3
+        - ❌
+        - ❌
+        - ✅
+        - ✅
+        - ❌
+        - ✅
+        - ✅
+
+      *
+        - RDNA3
+        - ❌
+        - ❌
+        - ✅
+        - ✅
+        - ❌
+        - ✅
+        - ✅
+
+      *
+        - RDNA4
         - ❌
         - ❌
         - ✅
@@ -271,19 +430,33 @@ The following table lists data type support for AMD GPU matrix cores.
         - int32
         - int64
       *
-        - MI100
+        - CDNA1
         - ✅
         - ❌
         - ❌
         - ❌
       *
-        - MI200 series
+        - CDNA2
         - ✅
         - ❌
         - ❌
         - ❌
       *
-        - MI300 series
+        - CDNA3
+        - ✅
+        - ❌
+        - ❌
+        - ❌
+
+      *
+        - RDNA3
+        - ✅
+        - ❌
+        - ❌
+        - ❌
+
+      *
+        - RDNA4
         - ✅
         - ❌
         - ❌
@@ -305,7 +478,7 @@ The following table lists data type support for AMD GPU matrix cores.
         - float32
         - float64
       *
-        - MI100
+        - CDNA1
         - ❌
         - ❌
         - ✅
@@ -314,7 +487,7 @@ The following table lists data type support for AMD GPU matrix cores.
         - ✅
         - ❌
       *
-        - MI200 series
+        - CDNA2
         - ❌
         - ❌
         - ✅
@@ -323,7 +496,7 @@ The following table lists data type support for AMD GPU matrix cores.
         - ✅
         - ✅
       *
-        - MI300 series
+        - CDNA3
         - ✅
         - ✅
         - ✅
@@ -332,6 +505,26 @@ The following table lists data type support for AMD GPU matrix cores.
         - ✅
         - ✅
 
+      *
+        - RDNA3
+        - ❌
+        - ❌
+        - ✅
+        - ✅
+        - ❌
+        - ❌
+        - ❌
+
+      *
+        - RDNA4
+        - ✅
+        - ✅
+        - ✅
+        - ✅
+        - ❌
+        - ❌
+        - ❌
+
 Atomic operations support
 -------------------------
 
@@ -357,19 +550,33 @@ page.
         - int32
         - int64
       *
-        - MI100
+        - CDNA1
         - ❌
         - ❌
         - ✅
         - ✅
       *
-        - MI200 series
+        - CDNA2
         - ❌
         - ❌
         - ✅
         - ✅
       *
-        - MI300 series
+        - CDNA3
+        - ❌
+        - ❌
+        - ✅
+        - ✅
+
+      *
+        - RDNA3
+        - ❌
+        - ❌
+        - ✅
+        - ✅
+
+      *
+        - RDNA4
         - ❌
         - ❌
         - ✅
@@ -391,7 +598,7 @@ page.
         - float32
         - float64
       *
-        - MI100
+        - CDNA1
         - ❌
         - ❌
         - ✅
@@ -400,7 +607,7 @@ page.
         - ✅
         - ❌
       *
-        - MI200 series
+        - CDNA2
         - ❌
         - ❌
         - ✅
@@ -409,7 +616,7 @@ page.
         - ✅
         - ✅
       *
-        - MI300 series
+        - CDNA3
         - ❌
         - ❌
         - ✅
@@ -418,6 +625,26 @@ page.
         - ✅
         - ✅
 
+      *
+        - RDNA3
+        - ❌
+        - ❌
+        - ❌
+        - ❌
+        - ❌
+        - ✅
+        - ❌
+
+      *
+        - RDNA4
+        - ❌
+        - ❌
+        - ✅
+        - ✅
+        - ❌
+        - ✅
+        - ❌
+
 .. note::
 
   You can emulate atomic operations using software for cases that are not
@@ -452,36 +679,98 @@ detailed description.
         - int16
         - int32
         - int64
+
       *
-        - :doc:`hipSPARSELt <hipsparselt:reference/data-type-support>`
+        - :doc:`Composable Kernel <composable_kernel:reference/Composable_Kernel_supported_scalar_types>`
         - ✅/✅
         - ❌/❌
+        - ✅/✅
         - ❌/❌
-        - ❌/❌
-      *
-        - :doc:`rocRAND <rocrand:api-reference/data-type-support>`
-        - NA/✅
-        - NA/✅
-        - NA/✅
-        - NA/✅
-      *
-        - :doc:`hipRAND <hiprand:api-reference/data-type-support>`
-        - NA/✅
-        - NA/✅
-        - NA/✅
-        - NA/✅
-      *
-        -  :doc:`rocPRIM <rocprim:reference/data-type-support>`
-        - ✅/✅
-        - ✅/✅
-        - ✅/✅
-        - ✅/✅
+
       *
         - :doc:`hipCUB <hipcub:api-reference/data-type-support>`
         - ✅/✅
         - ✅/✅
         - ✅/✅
         - ✅/✅
+
+      *
+        - :doc:`hipRAND <hiprand:api-reference/data-type-support>`
+        - NA/✅
+        - NA/✅
+        - NA/✅
+        - NA/✅
+
+      *
+        - :doc:`hipSOLVER <hipsolver:reference/precision>`
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+
+      *
+        - :doc:`hipSPARSELt <hipsparselt:reference/data-type-support>`
+        - ✅/✅
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+
+      *
+        - :doc:`hipTensor <hiptensor:api-reference/api-reference>`
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+
+      *
+        - :doc:`MIGraphX <amdmigraphx:reference/cpp>`
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`MIOpen <miopen:reference/datatypes>`
+        - ⚠️/⚠️
+        - ❌/❌
+        - ⚠️/⚠️
+        - ❌/❌
+
+      *
+        - :doc:`RCCL <rccl:api-reference/library-specification>`
+        - ✅/✅
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`rocFFT <rocfft:reference/api>`
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+
+      *
+        -  :doc:`rocPRIM <rocprim:reference/data-type-support>`
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`rocRAND <rocrand:api-reference/data-type-support>`
+        - NA/✅
+        - NA/✅
+        - NA/✅
+        - NA/✅
+
+      *
+        - :doc:`rocSOLVER <rocsolver:reference/precision>`
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+
       *
         - :doc:`rocThrust <rocthrust:data-type-support>`
         - ✅/✅
@@ -489,6 +778,14 @@ detailed description.
         - ✅/✅
         - ✅/✅
 
+      *
+        - :doc:`rocWMMA <rocwmma:api-reference/api-reference-guide>`
+        - ✅/✅
+        - ❌/❌
+        - ❌/✅
+        - ❌/❌
+
+
   .. tab-item:: Floating-point types
     :sync: floating-point-type
 
@@ -504,42 +801,17 @@ detailed description.
         - tensorfloat32
         - float32
         - float64
+
       *
-        - :doc:`hipSPARSELt <hipsparselt:reference/data-type-support>`
-        - ❌/❌
-        - ❌/❌
+        - :doc:`Composable Kernel <composable_kernel:reference/Composable_Kernel_supported_scalar_types>`
         - ✅/✅
         - ✅/✅
-        - ❌/❌
-        - ❌/❌
-        - ❌/❌
-      *
-        - :doc:`rocRAND <rocrand:api-reference/data-type-support>`
-        - NA/❌
-        - NA/❌
-        - NA/✅
-        - NA/❌
-        - NA/❌
-        - NA/✅
-        - NA/✅
-      *
-        - :doc:`hipRAND <hiprand:api-reference/data-type-support>`
-        - NA/❌
-        - NA/❌
-        - NA/✅
-        - NA/❌
-        - NA/❌
-        - NA/✅
-        - NA/✅
-      *
-        - :doc:`rocPRIM <rocprim:reference/data-type-support>`
-        - ❌/❌
-        - ❌/❌
         - ✅/✅
         - ✅/✅
         - ❌/❌
         - ✅/✅
         - ✅/✅
+
       *
         - :doc:`hipCUB <hipcub:api-reference/data-type-support>`
         - ❌/❌
@@ -549,6 +821,117 @@ detailed description.
         - ❌/❌
         - ✅/✅
         - ✅/✅
+
+      *
+        - :doc:`hipRAND <hiprand:api-reference/data-type-support>`
+        - NA/❌
+        - NA/❌
+        - NA/✅
+        - NA/❌
+        - NA/❌
+        - NA/✅
+        - NA/✅
+
+      *
+        - :doc:`hipSOLVER <hipsolver:reference/precision>`
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`hipSPARSELt <hipsparselt:reference/data-type-support>`
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+
+      *
+        - :doc:`hipTensor <hiptensor:api-reference/api-reference>`
+        - ❌/❌
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`MIGraphX <amdmigraphx:reference/cpp>`
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`MIOpen <miopen:reference/datatypes>`
+        - ⚠️/⚠️
+        - ⚠️/⚠️
+        - ✅/✅
+        - ⚠️/⚠️
+        - ❌/❌
+        - ✅/✅
+        - ⚠️/⚠️
+
+      *
+        - :doc:`RCCL <rccl:api-reference/library-specification>`
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`rocFFT <rocfft:reference/api>`
+        - ❌/❌
+        - ❌/❌
+        - ✅/✅
+        - ❌/❌
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`rocPRIM <rocprim:reference/data-type-support>`
+        - ❌/❌
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+
+      *
+        - :doc:`rocRAND <rocrand:api-reference/data-type-support>`
+        - NA/❌
+        - NA/❌
+        - NA/✅
+        - NA/❌
+        - NA/❌
+        - NA/✅
+        - NA/✅
+
+      *
+        - :doc:`rocSOLVER <rocsolver:reference/precision>`
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ❌/❌
+        - ✅/✅
+        - ✅/✅
+
       *
         - :doc:`rocThrust <rocthrust:data-type-support>`
         - ❌/❌
@@ -559,62 +942,123 @@ detailed description.
         - ✅/✅
         - ✅/✅
 
+      *
+        - :doc:`rocWMMA <rocwmma:api-reference/api-reference-guide>`
+        - ✅/❌
+        - ✅/❌
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+        - ✅/✅
+
 .. note::
-   
+
   As random number generation libraries, rocRAND and hipRAND only specify output
   data types for the random values they generate, with no need for input data
   types.
 
-Libraries internal calculations type support
---------------------------------------------
+hipDataType enumeration
+-----------------------
 
-The following tables list ROCm library support for specific internal data types.
-Refer to the corresponding library data type support page for a detailed
-description.
+The ``hipDataType`` enumeration defines data precision types and is primarily
+used when the data reference itself does not include type information, such as
+in ``void*`` pointers. This enumeration is mainly utilized in BLAS libraries.
+The HIP type equivalents of the ``hipDataType`` enumeration are listed in the
+following table with descriptions and values.
 
-.. tab-set::
+.. list-table::
+    :header-rows: 1
+    :widths: 25,25,10,40
 
-  .. tab-item:: Integral types
-    :sync: integral-type
+    *
+      - hipDataType
+      - HIP type
+      - Value
+      - Description
 
-    .. list-table::
-      :header-rows: 1
+    *
+      - ``HIP_R_8I``
+      - ``int8_t``
+      - 3
+      - 8-bit real signed integer.
 
-      *
-        - Library internal data type name
-        - int8
-        - int16
-        - int32
-        - int64
-      *
-        - :doc:`hipSPARSELt <hipsparselt:reference/data-type-support>`
-        - ❌
-        - ❌
-        - ✅
-        - ❌
+    *
+      - ``HIP_R_8U``
+      - ``uint8_t``
+      - 8
+      - 8-bit real unsigned integer.
 
+    *
+      - ``HIP_R_16I``
+      - ``int16_t``
+      - 20
+      - 16-bit real signed integer.
 
-  .. tab-item:: Floating-point types
-    :sync: floating-point-type
+    *
+      - ``HIP_R_16U``
+      - ``uint16_t``
+      - 22
+      - 16-bit real unsigned integer.
 
-    .. list-table::
-      :header-rows: 1
+    *
+      - ``HIP_R_32I``
+      - ``int32_t``
+      - 10
+      - 32-bit real signed integer.
 
-      *
-        - Library internal data type name
-        - float8 (E4M3)
-        - float8 (E5M2)
-        - float16
-        - bfloat16
-        - tensorfloat32
-        - float32
-        - float64
-      *
-        - :doc:`hipSPARSELt <hipsparselt:reference/data-type-support>`
-        - ❌
-        - ❌
-        - ❌
-        - ❌
-        - ❌
-        - ✅
-        - ❌
+    *
+      - ``HIP_R_32U``
+      - ``uint32_t``
+      - 12
+      - 32-bit real unsigned integer.
+
+    *
+      - ``HIP_R_32F``
+      - ``float``
+      - 0
+      - 32-bit real single precision floating-point.
+
+    *
+      - ``HIP_R_64F``
+      - ``double``
+      - 1
+      - 64-bit real double precision floating-point.
+
+    *
+      - ``HIP_R_16F``
+      - ``half``
+      - 2
+      - 16-bit real half precision floating-point.
+
+    *
+      - ``HIP_R_16BF``
+      - ``bfloat16``
+      - 14
+      - 16-bit real bfloat16 precision floating-point.
+
+    *
+      - ``HIP_R_8F_E4M3``
+      - ``__hip_fp8_e4m3``
+      - 28
+      - 8-bit real float8 precision floating-point (OCP version).
+
+    *
+      - ``HIP_R_8F_E5M2``
+      - ``__hip_fp8_e5m2``
+      - 29
+      - 8-bit real bfloat8 precision floating-point (OCP version).
+
+    *
+      - ``HIP_R_8F_E4M3_FNUZ``
+      - ``__hip_fp8_e4m3_fnuz``
+      - 1000
+      - 8-bit real float8 precision floating-point (FNUZ version).
+
+    *
+      - ``HIP_R_8F_E5M2_FNUZ``
+      - ``__hip_fp8_e5m2_fnuz``
+      - 1001
+      - 8-bit real bfloat8 precision floating-point (FNUZ version).
+
+The full list of the ``hipDataType`` enumeration listed in `library_types.h <https://github.com/ROCm/hip/blob/amd-staging/include/hip/library_types.h>`_ .

docs/release/versions.md

@@ -10,6 +10,7 @@
 
 | Version | Release date |
 | ------- | ------------ |
+| [6.4.3](https://rocm.docs.amd.com/en/docs-6.4.3/) | August 7, 2025 |
 | [6.4.2](https://rocm.docs.amd.com/en/docs-6.4.2/) | July 21, 2025 |
 | [6.4.1](https://rocm.docs.amd.com/en/docs-6.4.1/) | May 21, 2025 |
 | [6.4.0](https://rocm.docs.amd.com/en/docs-6.4.0/) | April 11, 2025 |

docs/sphinx/_toc.yml.in

@@ -19,14 +19,32 @@ subtrees:
 
 - caption: Install
   entries:
-  - url: https://rocm.docs.amd.com/projects/install-on-linux/en/latest/
+  - url: https://rocm.docs.amd.com/projects/install-on-linux/en/${branch}/
     title: ROCm on Linux
-  - url: https://rocm.docs.amd.com/projects/install-on-windows/en/${branch}/
+  - url: https://rocm.docs.amd.com/projects/install-on-windows/en/latest/
     title: HIP SDK on Windows
   - url: https://rocm.docs.amd.com/projects/radeon/en/latest/index.html
     title: ROCm on Radeon GPUs
   - file: how-to/deep-learning-rocm.md
     title: Deep learning frameworks
+    subtrees:
+    - entries:
+      - file: compatibility/ml-compatibility/pytorch-compatibility.rst
+        title: PyTorch compatibility
+      - file: compatibility/ml-compatibility/tensorflow-compatibility.rst
+        title: TensorFlow compatibility  
+      - file: compatibility/ml-compatibility/jax-compatibility.rst
+        title: JAX compatibility
+      - file: compatibility/ml-compatibility/verl-compatibility.rst
+        title: verl compatibility  
+      - file: compatibility/ml-compatibility/stanford-megatron-lm-compatibility.rst
+        title: Stanford Megatron-LM compatibility
+      - file: compatibility/ml-compatibility/dgl-compatibility.rst
+        title: DGL compatibility  
+      - file: compatibility/ml-compatibility/megablocks-compatibility.rst
+        title: Megablocks compatibility
+      - file: compatibility/ml-compatibility/taichi-compatibility.rst
+        title: Taichi compatibility 
   - file: how-to/build-rocm.rst
     title: Build ROCm from source
 
@@ -44,8 +62,8 @@ subtrees:
         title: Training
         subtrees:
         - entries:
-          - file: how-to/rocm-for-ai/training/benchmark-docker/megatron-lm.rst
-            title: Train a model with Megatron-LM
+          - file: how-to/rocm-for-ai/training/benchmark-docker/primus-megatron.rst
+            title: Train a model with Primus and Megatron-Core
           - file: how-to/rocm-for-ai/training/benchmark-docker/pytorch-training.rst
             title: Train a model with PyTorch
           - file: how-to/rocm-for-ai/training/benchmark-docker/jax-maxtext.rst
@@ -82,6 +100,8 @@ subtrees:
             title: vLLM inference performance testing
           - file: how-to/rocm-for-ai/inference/benchmark-docker/pytorch-inference.rst
             title: PyTorch inference performance testing
+          - file: how-to/rocm-for-ai/inference/benchmark-docker/sglang.rst
+            title: SGLang inference performance testing
           - file: how-to/rocm-for-ai/inference/deploy-your-model.rst
             title: Deploy your model
 

docs/sphinx/requirements.in

@@ -1,4 +1,4 @@
-rocm-docs-core==1.20.1
+rocm-docs-core==1.22.0
 sphinx-reredirects
 sphinx-sitemap
 sphinxcontrib.datatemplates==0.11.0

docs/sphinx/requirements.txt

@@ -23,7 +23,7 @@ beautifulsoup4==4.13.4
     # via pydata-sphinx-theme
 breathe==4.36.0
     # via rocm-docs-core
-certifi==2025.4.26
+certifi==2025.7.14
     # via requests
 cffi==1.17.1
     # via
@@ -35,18 +35,16 @@ click==8.2.1
     # via
     #   jupyter-cache
     #   sphinx-external-toc
-comm==0.2.2
+comm==0.2.3
     # via ipykernel
-cryptography==45.0.3
+cryptography==45.0.5
     # via pyjwt
-debugpy==1.8.14
+debugpy==1.8.15
     # via ipykernel
 decorator==5.2.1
     # via ipython
 defusedxml==0.7.1
     # via sphinxcontrib-datatemplates
-deprecated==1.2.18
-    # via pygithub
 docutils==0.21.2
     # via
     #   myst-parser
@@ -62,7 +60,7 @@ fastjsonschema==2.21.1
     #   rocm-docs-core
 gitdb==4.0.12
     # via gitpython
-gitpython==3.1.44
+gitpython==3.1.45
     # via rocm-docs-core
 greenlet==3.2.3
     # via sqlalchemy
@@ -74,7 +72,7 @@ importlib-metadata==8.7.0
     # via
     #   jupyter-cache
     #   myst-nb
-ipykernel==6.29.5
+ipykernel==6.30.0
     # via myst-nb
 ipython==8.37.0
     # via
@@ -86,7 +84,7 @@ jinja2==3.1.6
     # via
     #   myst-parser
     #   sphinx
-jsonschema==4.24.0
+jsonschema==4.25.0
     # via nbformat
 jsonschema-specifications==2025.4.1
     # via jsonschema
@@ -116,7 +114,7 @@ mdit-py-plugins==0.4.2
     # via myst-parser
 mdurl==0.1.2
     # via markdown-it-py
-myst-nb==1.2.0
+myst-nb==1.3.0
     # via rocm-docs-core
 myst-parser==4.0.1
     # via myst-nb
@@ -134,7 +132,6 @@ nest-asyncio==1.6.0
 packaging==25.0
     # via
     #   ipykernel
-    #   pydata-sphinx-theme
     #   sphinx
 parso==0.8.4
     # via jedi
@@ -152,13 +149,13 @@ pure-eval==0.2.3
     # via stack-data
 pycparser==2.22
     # via cffi
-pydata-sphinx-theme==0.15.4
+pydata-sphinx-theme==0.16.1
     # via
     #   rocm-docs-core
     #   sphinx-book-theme
-pygithub==2.6.1
+pygithub==2.7.0
     # via rocm-docs-core
-pygments==2.19.1
+pygments==2.19.2
     # via
     #   accessible-pygments
     #   ipython
@@ -178,7 +175,7 @@ pyyaml==6.0.2
     #   rocm-docs-core
     #   sphinx-external-toc
     #   sphinxcontrib-datatemplates
-pyzmq==26.4.0
+pyzmq==27.0.0
     # via
     #   ipykernel
     #   jupyter-client
@@ -190,9 +187,9 @@ requests==2.32.4
     # via
     #   pygithub
     #   sphinx
-rocm-docs-core==1.20.1
+rocm-docs-core==1.22.0
     # via -r requirements.in
-rpds-py==0.25.1
+rpds-py==0.26.0
     # via
     #   jsonschema
     #   referencing
@@ -220,7 +217,7 @@ sphinx==8.1.3
     #   sphinx-reredirects
     #   sphinxcontrib-datatemplates
     #   sphinxcontrib-runcmd
-sphinx-book-theme==1.1.4
+sphinx-book-theme==1.1.3
     # via rocm-docs-core
 sphinx-copybutton==0.5.2
     # via rocm-docs-core
@@ -252,7 +249,7 @@ sphinxcontrib-runcmd==0.2.0
     # via sphinxcontrib-datatemplates
 sphinxcontrib-serializinghtml==2.0.0
     # via sphinx
-sqlalchemy==2.0.41
+sqlalchemy==2.0.42
     # via jupyter-cache
 stack-data==0.6.3
     # via ipython
@@ -266,7 +263,6 @@ tornado==6.5.1
     #   jupyter-client
 traitlets==5.14.3
     # via
-    #   comm
     #   ipykernel
     #   ipython
     #   jupyter-client
@@ -274,7 +270,7 @@ traitlets==5.14.3
     #   matplotlib-inline
     #   nbclient
     #   nbformat
-typing-extensions==4.14.0
+typing-extensions==4.14.1
     # via
     #   beautifulsoup4
     #   exceptiongroup
@@ -290,7 +286,5 @@ urllib3==2.5.0
     #   requests
 wcwidth==0.2.13
     # via prompt-toolkit
-wrapt==1.17.2
-    # via deprecated
 zipp==3.23.0
     # via importlib-metadata