Docs: Fix gpu-arch-spec.rst

Ex CI: set ROCM_PATH for MIOpen tests (#4371 )
Merge pull request #4350 from ROCm/docs_device_version
2026-01-09 22:58:17 -05:00 · 2025-02-19 17:05:01 +01:00 · 2025-02-13 16:03:56 -05:00 · 2025-02-13 14:41:01 +01:00 · 2025-02-13 14:24:00 +01:00 · 2025-02-12 11:36:53 -05:00
37 changed files with 583 additions and 259 deletions
--- a/.azuredevops/components/MIOpen.yml
+++ b/.azuredevops/components/MIOpen.yml
@@ -101,7 +101,7 @@ jobs:
        -DMIOPEN_BACKEND=HIP
        -DCMAKE_CXX_COMPILER=$(Agent.BuildDirectory)/rocm/llvm/bin/amdclang++
        -DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm;$(Agent.BuildDirectory)/miopen-deps
-        -DAMDGPU_TARGETS=$(JOB_GPU_TARGET)
+        -DGPU_TARGETS=$(JOB_GPU_TARGET)
        -DMIOPEN_ENABLE_AI_KERNEL_TUNING=OFF
        -DMIOPEN_ENABLE_AI_IMMED_MODE_FALLBACK=OFF
        -DCMAKE_BUILD_TYPE=Release
@@ -129,6 +129,8 @@ jobs:
  variables:
  - group: common
  - template: /.azuredevops/variables-global.yml
+  - name: ROCM_PATH
+    value: $(Agent.BuildDirectory)/rocm
  pool: $(JOB_TEST_POOL)
  workspace:
    clean: all
--- a/.azuredevops/components/ROCR-Runtime.yml
+++ b/.azuredevops/components/ROCR-Runtime.yml
@@ -123,16 +123,13 @@ jobs:
      targetType: 'inline'
      workingDirectory: $(Build.SourcesDirectory)/rocrtst/suites/test_common
      script: |
-        sudo rm -rf $(Agent.BuildDirectory)/external/llvm-project
-        mkdir -p $(Agent.BuildDirectory)/external/llvm-project/clang/lib
-        sudo ln -s $(Agent.BuildDirectory)/rocm/llvm/lib/clang/20/include $(Agent.BuildDirectory)/external/llvm-project/clang/lib/Headers
        mkdir build && cd build
        cmake .. \
          -DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm \
          -DTARGET_DEVICES=$(JOB_GPU_TARGET) \
          -DROCM_DIR=$(Agent.BuildDirectory)/rocm \
          -DLLVM_DIR=$(Agent.BuildDirectory)/rocm/llvm/bin \
-          -DOPENCL_DIR=$(Agent.BuildDirectory)/rocm/llvm/bin
+          -DOPENCL_INC_DIR=$(Agent.BuildDirectory)/rocm/llvm/lib/clang/21/include
        make
        make rocrtst_kernels
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
--- a/.azuredevops/components/hipBLASLt.yml
+++ b/.azuredevops/components/hipBLASLt.yml
@@ -59,14 +59,10 @@ jobs:
    value: $(Build.BinariesDirectory)/rocm
  - name: TENSILE_ROCM_ASSEMBLER_PATH
    value: $(Agent.BuildDirectory)/rocm/llvm/bin/amdclang
-  - name: CMAKE_CXX_COMPILER
-    value: $(Agent.BuildDirectory)/rocm/bin/hipcc
  - name: TENSILE_ROCM_OFFLOAD_BUNDLER_PATH
    value: $(Agent.BuildDirectory)/rocm/llvm/bin/clang-offload-bundler
-  - name: TENSILE_ROCM_PATH
-    value: $(Agent.BuildDirectory)/rocm/bin/hipcc
-  - name: PATH
-    value: $(Agent.BuildDirectory)/rocm/llvm/bin:$(Agent.BuildDirectory)/rocm/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/snap/bin
+  - name: ROCM_PATH
+    value: $(Agent.BuildDirectory)/rocm
  - name: DAY_STRING
    value: $[format('{0:ddMMyyyy}', pipeline.startTime)]
  pool: ${{ variables.ULTRA_BUILD_POOL }}
@@ -154,9 +150,8 @@ jobs:
      extraEnvVars:
        - HIP_ROCCLR_HOME:::/home/user/workspace/rocm
        - TENSILE_ROCM_ASSEMBLER_PATH:::/home/user/workspace/rocm/llvm/bin/amdclang
-        - CMAKE_CXX_COMPILER:::/home/user/workspace/rocm/bin/hipcc
        - TENSILE_ROCM_OFFLOAD_BUNDLER_PATH:::/home/user/workspace/rocm/llvm/bin/clang-offload-bundler
-        - TENSILE_ROCM_PATH:::/home/user/workspace/rocm/bin/hipcc
+        - ROCM_PATH:::/home/user/workspace/rocm
      extraCopyDirectories:
        - deps

--- a/.azuredevops/components/rccl.yml
+++ b/.azuredevops/components/rccl.yml
@@ -51,6 +51,7 @@ parameters:

 jobs:
 - job: rccl
+  timeoutInMinutes: 90
  variables:
  - group: common
  - template: /.azuredevops/variables-global.yml
@@ -78,7 +79,6 @@ jobs:
      checkoutRef: ${{ parameters.checkoutRef }}
      dependencyList: ${{ parameters.rocmDependencies }}
      gpuTarget: $(JOB_GPU_TARGET)
-  - script: chmod +x $(Agent.BuildDirectory)/rocm/bin/hipify-perl
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
    parameters:
      extraBuildFlags: >-
@@ -88,7 +88,7 @@ jobs:
        -DCMAKE_BUILD_TYPE=Release
        -DROCM_PATH=$(Agent.BuildDirectory)/rocm
        -DBUILD_TESTS=ON
-        -DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm;$(Agent.BuildDirectory)/rocm/share/rocm/cmake/
+        -DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm;$(Agent.BuildDirectory)/rocm/share/rocm/cmake;$(Agent.BuildDirectory)/rocm/libexec/hipify
        -DAMDGPU_TARGETS=$(JOB_GPU_TARGET)
        -GNinja
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
--- a/.azuredevops/components/rocBLAS.yml
+++ b/.azuredevops/components/rocBLAS.yml
@@ -64,10 +64,10 @@ jobs:
    value: $(Build.BinariesDirectory)/rocm
  - name: TENSILE_ROCM_ASSEMBLER_PATH
    value: $(Agent.BuildDirectory)/rocm/llvm/bin/clang
-  - name: CMAKE_CXX_COMPILER
-    value: $(Agent.BuildDirectory)/rocm/bin/hipcc
  - name: TENSILE_ROCM_OFFLOAD_BUNDLER_PATH
    value: $(Agent.BuildDirectory)/rocm/llvm/bin/clang-offload-bundler
+  - name: ROCM_PATH
+    value: $(Agent.BuildDirectory)/rocm
  pool: ${{ variables.MEDIUM_BUILD_POOL }}
  workspace:
    clean: all
@@ -96,8 +96,8 @@ jobs:
        -DCMAKE_TOOLCHAIN_FILE=toolchain-linux.cmake
        -DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm/llvm;$(Agent.BuildDirectory)/rocm
        -DCMAKE_BUILD_TYPE=Release
-        -DCMAKE_CXX_COMPILER=$(Agent.BuildDirectory)/rocm/bin/hipcc
-        -DCMAKE_C_COMPILER=$(Agent.BuildDirectory)/rocm/bin/hipcc
+        -DCMAKE_CXX_COMPILER=$(Agent.BuildDirectory)/rocm/bin/amdclang++
+        -DCMAKE_C_COMPILER=$(Agent.BuildDirectory)/rocm/bin/amdclang
        -DGPU_TARGETS=$(JOB_GPU_TARGET)
        -DTensile_CODE_OBJECT_VERSION=default
        -DTensile_LOGIC=asm_full
@@ -125,8 +125,8 @@ jobs:
      extraEnvVars:
        - HIP_ROCCLR_HOME:::/home/user/workspace/rocm
        - TENSILE_ROCM_ASSEMBLER_PATH:::/home/user/workspace/rocm/llvm/bin/clang
-        - CMAKE_CXX_COMPILER:::/home/user/workspace/rocm/bin/hipcc
        - TENSILE_ROCM_OFFLOAD_BUNDLER_PATH:::/home/user/workspace/rocm/llvm/bin/clang-offload-bundler
+        - ROCM_PATH:::/home/user/workspace/rocm

 - job: rocBLAS_testing
  dependsOn: rocBLAS
--- a/.azuredevops/components/rocDecode.yml
+++ b/.azuredevops/components/rocDecode.yml
@@ -49,21 +49,10 @@ jobs:
  workspace:
    clean: all
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -104,21 +93,10 @@ jobs:
        JOB_GPU_TARGET: gfx942
        JOB_TEST_POOL: ${{ variables.GFX942_TEST_POOL }}
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
--- a/.azuredevops/components/rocJPEG.yml
+++ b/.azuredevops/components/rocJPEG.yml
@@ -48,21 +48,10 @@ jobs:
      gfx942:
        JOB_GPU_TARGET: gfx942
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -106,21 +95,10 @@ jobs:
        JOB_GPU_TARGET: gfx942
        JOB_TEST_POOL: ${{ variables.GFX942_TEST_POOL }}
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
--- a/.azuredevops/components/rocWMMA.yml
+++ b/.azuredevops/components/rocWMMA.yml
@@ -80,6 +80,7 @@ jobs:
        -DROCWMMA_BUILD_SAMPLES=OFF
        -DGPU_TARGETS=$(JOB_GPU_TARGET)
        -DCMAKE_BUILD_WITH_INSTALL_RPATH=ON
+        -DROCM_PLATFORM_VERSION=$(NEXT_RELEASE_VERSION)
        -GNinja
 # gfx1030 not supported in documentation
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
--- a/.azuredevops/components/rocm-core.yml
+++ b/.azuredevops/components/rocm-core.yml
@@ -36,7 +36,7 @@ jobs:
        -DCPACK_GENERATOR=DEB
        -DCPACK_DEBIAN_PACKAGE_RELEASE="local.9999~99.99"
        -DCPACK_RPM_PACKAGE_RELEASE="local.9999"
-        -DROCM_VERSION="$(next-release)"
+        -DROCM_VERSION="$(NEXT_RELEASE_VERSION)"
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
--- a/.azuredevops/components/rocminfo.yml
+++ b/.azuredevops/components/rocminfo.yml
@@ -35,7 +35,7 @@ jobs:
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -56,6 +56,7 @@ jobs:
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true

 - job: rocminfo_testing
  dependsOn: rocminfo
@@ -102,5 +103,6 @@ jobs:
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
      environment: test
      gpuTarget: $(JOB_GPU_TARGET)
--- a/.azuredevops/components/rocprofiler-sdk.yml
+++ b/.azuredevops/components/rocprofiler-sdk.yml
@@ -37,6 +37,8 @@ parameters:
    - clr
    - llvm-project
    - rccl
+    - rocDecode
+    - rocJPEG
    - rocm-cmake
    - rocm-core
    - rocminfo
@@ -60,7 +62,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -99,6 +101,7 @@ jobs:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
      gpuTarget: $(JOB_GPU_TARGET)
+      registerROCmPackages: true

 - job: rocprofiler_sdk_testing
  dependsOn: rocprofiler_sdk
@@ -119,7 +122,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -155,3 +158,4 @@ jobs:
      pipModules: ${{ parameters.pipModules }}
      environment: test
      gpuTarget: $(JOB_GPU_TARGET)
+      registerROCmPackages: true
--- a/.azuredevops/components/rocprofiler-systems.yml
+++ b/.azuredevops/components/rocprofiler-systems.yml
@@ -46,17 +46,19 @@ parameters:
 - name: rocmDependencies
  type: object
  default:
+    - amdsmi
    - aomp
    - clr
    - llvm-project
    - rccl
    - rocDecode
+    - rocJPEG
    - rocm-core
-    - rocm_smi_lib
    - rocminfo
-    - ROCR-Runtime
+    - rocm_smi_lib
    - rocprofiler-register
    - rocprofiler-sdk
+    - ROCR-Runtime

 jobs:
 - job: rocprofiler_systems
@@ -75,7 +77,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -159,7 +161,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
--- a/.azuredevops/dependencies/half560.yml
+++ b/.azuredevops/dependencies/half560.yml
@@ -19,7 +19,7 @@ jobs:
  pool:
    vmImage: ${{ variables.BASE_BUILD_POOL }}
  container:
-    image: ${{ variables.DOCKER_IMAGE_NAME }}:${{ variables.LATEST_DOCKER_VERSION }}
+    image: rocm/dev-ubuntu-22.04:${{ variables.LATEST_RELEASE_VERSION }}
  workspace:
    clean: all
  steps:
--- a/.azuredevops/templates/steps/dependencies-aqlprofile.yml
+++ b/.azuredevops/templates/steps/dependencies-aqlprofile.yml
@@ -4,13 +4,13 @@ steps:
  inputs:
    targetType: inline
    script: |
-      export packageName=$(curl -s https://repo.radeon.com/rocm/apt/latest/pool/main/h/hsa-amd-aqlprofile/ | grep -oP "href=\"\K[^\"]*$(lsb_release -rs)[^\"]*\.deb")
+      export packageName=$(curl -s https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION)/pool/main/h/hsa-amd-aqlprofile/ | grep -oP "href=\"\K[^\"]*$(lsb_release -rs)[^\"]*\.deb")
      echo "##vso[task.setvariable variable=packageName;isreadonly=true]$packageName"
 - task: Bash@3
  displayName: 'Download aqlprofile'
  inputs:
    targetType: inline
-    script: wget -nv https://repo.radeon.com/rocm/apt/latest/pool/main/h/hsa-amd-aqlprofile/$(packageName)
+    script: wget -nv https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION)/pool/main/h/hsa-amd-aqlprofile/$(packageName)
    workingDirectory: '$(Pipeline.Workspace)'
 - task: Bash@3
  displayName: 'Extract aqlprofile'
--- a/.azuredevops/templates/steps/dependencies-other.yml
+++ b/.azuredevops/templates/steps/dependencies-other.yml
@@ -6,21 +6,21 @@ parameters:
 - name: pipModules
  type: object
  default: []
- name: registerRadeon
+- name: registerROCmPackages
  type: boolean
  default: false

 steps:
- ${{ if eq(parameters.registerRadeon, true) }}:
+- ${{ if eq(parameters.registerROCmPackages, true) }}:
  - task: Bash@3
-    displayName: 'Register repo.radeon packages'
+    displayName: 'Register AMDGPU & ROCm repos'
    inputs:
      targetType: inline
      script: |
        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/latest/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/latest jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
+        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/$(REPO_RADEON_VERSION)/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
+        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION) jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
        sudo apt update
 # firefox takes time to upgrade and is not needed for CI workloads, hold version
--- a/.azuredevops/templates/steps/docker-container.yml
+++ b/.azuredevops/templates/steps/docker-container.yml
@@ -154,8 +154,8 @@ steps:
        script: |
          echo "RUN mkdir --parents --mode=0755 /etc/apt/keyrings" >> Dockerfile
          echo "RUN wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | tee /etc/apt/keyrings/rocm.gpg > /dev/null" >> Dockerfile
-          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/latest/ubuntu jammy main\" | tee /etc/apt/sources.list.d/amdgpu.list" >> Dockerfile
-          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/latest jammy main\" | tee --append /etc/apt/sources.list.d/rocm.list" >> Dockerfile
+          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/$(REPO_RADEON_VERSION)/ubuntu jammy main\" | tee /etc/apt/sources.list.d/amdgpu.list" >> Dockerfile
+          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION) jammy main\" | tee --append /etc/apt/sources.list.d/rocm.list" >> Dockerfile
          echo "RUN printf 'Package: *\\nPin: release o=repo.radeon.com\\nPin-Priority: 600' > /etc/apt/preferences.d/rocm-pin-600" >> Dockerfile
          echo "RUN DEBIAN_FRONTEND=noninteractive apt-get --yes update" >> Dockerfile
  - ${{ if eq(parameters.registerCUDAPackages, true) }}:
--- a/.azuredevops/variables-global.yml
+++ b/.azuredevops/variables-global.yml
@@ -27,14 +27,14 @@ variables:
  value: rocm-ci_larger_base_disk_pool
 - name: GFX942_TEST_POOL
  value: gfx942_test_pool
+- name: LATEST_RELEASE_VERSION
+  value: 6.3.2
+- name: REPO_RADEON_VERSION
+  value: 6.3.2
+- name: NEXT_RELEASE_VERSION
+  value: 6.4.0
 - name: LATEST_RELEASE_TAG
-  value: rocm-6.1.0
- name: DOCKER_IMAGE_NAME
-  value: rocm/dev-ubuntu-22.04
- name: LATEST_DOCKER_VERSION
-  value: 6.1
- name: KEYRING_VERSION
-  value: 6.3
+  value: rocm-6.3.2
 - name: AMDMIGRAPHX_GFX942_TEST_PIPELINE_ID
  value: 197
 - name: AMDMIGRAPHX_PIPELINE_ID
@@ -151,8 +151,6 @@ variables:
  value: 105
 - name: HIPTENSOR_TAGGED_PIPELINE_ID
  value: 56
- name: LAST_RELEASE
-  value: 6.1.0
 - name: LLVM_PROJECT_PIPELINE_ID
  value: 2
 - name: LLVM_PROJECT_TAGGED_PIPELINE_ID
@@ -183,10 +181,6 @@ variables:
  value: 100
 - name: RDC_TAGGED_PIPELINE_ID
  value: 59
- name: REIMAGE_ORG
-  value: AGS-ROCm-CI
- name: REIMAGE_REPO
-  value: cirrascale-reimage-automation
 - name: ROCAL_PIPELINE_ID
  value: 151
 - name: ROCALUTION_GFX942_TEST_PIPELINE_ID
--- a/.github/workflows/issue_retrieval.yml
+++ b/.github/workflows/issue_retrieval.yml
@@ -2,7 +2,7 @@ name: Issue retrieval

 on:
  issues:
-    types: [opened]
+    types: [opened, edited]

 jobs:
  auto-retrieve:
@@ -15,7 +15,7 @@ jobs:
          app_id: ${{ secrets.ACTION_APP_ID }}
          private_key: ${{ secrets.ACTION_PEM }}
      - name: 'Retrieve Issue'
-        uses: abhimeda/rocm_issue_management@main
+        uses: harkgill-amd/rocm_issue_management@main
        with:
          authentication-token: ${{ steps.generate_token.outputs.token }}
          github-organization: 'ROCm'
--- a/.wordlist.txt
+++ b/.wordlist.txt
@@ -74,6 +74,7 @@ Conda
 ConnectX
 CuPy
 Dashboarding
+DBRX
 DDR
 DF
 DGEMM
@@ -92,6 +93,7 @@ DataFrame
 DataLoader
 DataParallel
 Debian
+DeepSeek
 DeepSpeed
 Dependabot
 Deprecations
@@ -129,6 +131,8 @@ GDS
 GEMM
 GEMMs
 GFortran
+GFXIP
+Gemma
 GiB
 GIM
 GL
--- a/RELEASE.md
+++ b/RELEASE.md
@@ -29,8 +29,7 @@ The release notes provide a summary of notable changes since the previous ROCm r
 - [ROCm upcoming changes](#rocm-upcoming-changes)

 ```{note}
-If you’re using Radeon™ PRO or Radeon GPUs in a workstation setting with a
-display connected, continue to use ROCm 6.2.3. See the [Use ROCm on Radeon GPUs](https://rocm.docs.amd.com/projects/radeon/en/latest/index.html)
+If you’re using Radeon™ PRO or Radeon GPUs in a workstation setting with a display connected, see the [Use ROCm on Radeon GPUs](https://rocm.docs.amd.com/projects/radeon/en/latest/docs/compatibility/native_linux/native_linux_compatibility.html)
 documentation to verify compatibility and system requirements.
 ```
 ## Release highlights
--- a/docs/about/license.md
+++ b/docs/about/license.md
@@ -62,7 +62,7 @@ additional licenses. Please review individual repositories for more information.
 | [rocJPEG](https://github.com/ROCm/rocJPEG/) | [MIT](https://github.com/ROCm/rocJPEG/blob/develop/LICENSE) |
 | [ROCK-Kernel-Driver](https://github.com/ROCm/ROCK-Kernel-Driver/) | [GPL 2.0 WITH Linux-syscall-note](https://github.com/ROCm/ROCK-Kernel-Driver/blob/master/COPYING) |
 | [rocminfo](https://github.com/ROCm/rocminfo/) | [The University of Illinois/NCSA](https://github.com/ROCm/rocminfo/blob/amd-staging/License.txt) |
-| [ROCm Bandwidth Test](https://github.com/ROCm/rocm_bandwidth_test/) | [The University of Illinois/NCSA](https://github.com/ROCm/rocm_bandwidth_test/blob/master/LICENSE.txt) |
+| [ROCm Bandwidth Test](https://github.com/ROCm/rocm_bandwidth_test/) | [MIT](https://github.com/ROCm/rocm_bandwidth_test/blob/master/LICENSE.txt) |
 | [ROCm CMake](https://github.com/ROCm/rocm-cmake/) | [MIT](https://github.com/ROCm/rocm-cmake/blob/develop/LICENSE) |
 | [ROCm Communication Collectives Library (RCCL)](https://github.com/ROCm/rccl/) | [Custom](https://github.com/ROCm/rccl/blob/develop/LICENSE.txt) |
 | [ROCm-Core](https://github.com/ROCm/rocm-core) | [MIT](https://github.com/ROCm/rocm-core/blob/master/copyright) |
--- a/docs/compatibility/compatibility-matrix-historical-6.0.csv
+++ b/docs/compatibility/compatibility-matrix-historical-6.0.csv
@@ -7,7 +7,7 @@ ROCm Version,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0, 6.1.2, 6.1.1, 6.1.0, 6.0
      ,"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"
      ,,,,,,,,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9
      ,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]_,,,
-,Debian 12 [#mi300x-past-60]_,Debian 12 [#mi300x-past-60]_,,,,,,,,,,
+,Debian 12 [#single-node-past-60]_,Debian 12 [#single-node-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
--- a/docs/compatibility/compatibility-matrix.rst
+++ b/docs/compatibility/compatibility-matrix.rst
@@ -32,7 +32,7 @@ compatibility and system requirements.
      ,RHEL 8.10,RHEL 8.10,"RHEL 8.10, 8.9"
      ,"SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5"
      ,Oracle Linux 8.10 [#mi300x]_,Oracle Linux 8.10 [#mi300x]_,Oracle Linux 8.9 [#mi300x]_
-      ,Debian 12 [#mi300x]_,Debian 12 [#mi300x]_,
+      ,Debian 12 [#single-node]_,Debian 12 [#single-node]_,
      ,Azure Linux 3.0 [#mi300x]_,,
      ,.. _architecture-support-compatibility-matrix:,,
      :doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA3,CDNA3,CDNA3
@@ -148,7 +148,8 @@ compatibility and system requirements.

 .. rubric:: Footnotes

-.. [#mi300x] Oracle Linux, Debian, and Azure Linux are supported only on AMD Instinct MI300X.
+.. [#mi300x] Oracle Linux and Azure Linux are supported only on AMD Instinct MI300X.
+.. [#single-node] Debian 12 is supported only on AMD Instinct MI300X for single-node functionality. 
 .. [#mi300_620] **For ROCm 6.2.0** - MI300X (gfx942) is supported on listed operating systems *except* Ubuntu 22.04.5 [6.8 HWE] and Ubuntu 22.04.4 [6.5 HWE].
 .. [#kfd_support] ROCm provides forward and backward compatibility between the AMD Kernel-mode GPU Driver (KMD) and its user space software for +/- 2 releases. These are the compatibility combinations that are currently supported.
 .. [#ROCT-rocr] Starting from ROCm 6.3.0, the ROCT Thunk Interface is included as part of the ROCr runtime package.
@@ -215,7 +216,8 @@ Expand for full historical view of:

   .. rubric:: Footnotes

-   .. [#mi300x-past-60] Oracle Linux, Debian, and Azure Linux are supported only on AMD Instinct MI300X.
+   .. [#mi300x-past-60] Oracle Linux and Azure Linux are supported only on AMD Instinct MI300X.
+   .. [#single-node-past-60] Debian 12 is supported only on AMD Instinct MI300X for single-node functionality. 
   .. [#mi300_624-past-60] **For ROCm 6.2.4** - MI300X (gfx942) is supported on listed operating systems *except* Ubuntu 22.04.5 [6.8 HWE] and Ubuntu 22.04.4 [6.5 HWE].
   .. [#mi300_622-past-60] **For ROCm 6.2.2** - MI300X (gfx942) is supported on listed operating systems *except* Ubuntu 22.04.5 [6.8 HWE] and Ubuntu 22.04.4 [6.5 HWE].
   .. [#mi300_621-past-60] **For ROCm 6.2.1** - MI300X (gfx942) is supported on listed operating systems *except* Ubuntu 22.04.5 [6.8 HWE] and Ubuntu 22.04.4 [6.5 HWE].
--- a/docs/how-to/rocm-for-ai/fine-tuning/index.rst
+++ b/docs/how-to/rocm-for-ai/fine-tuning/index.rst
@@ -16,6 +16,9 @@ Throughout the following topics, this guide discusses the goals and :ref:`challe
 model <fine-tuning-llms-concept-challenge>` like Llama 2. In the
 sections that follow, you'll find practical guides on libraries and tools to accelerate your fine-tuning.

+The AI Developer Hub contains `AMD ROCm tutorials <https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/>`_ for
+training, fine-tuning, and inference. It leverages popular machine learning frameworks on AMD GPUs.
+
 - :doc:`Conceptual overview of fine-tuning LLMs <overview>`

 - :doc:`Fine-tuning and inference <fine-tuning-and-inference>` using a
--- a/docs/how-to/rocm-for-ai/index.rst
+++ b/docs/how-to/rocm-for-ai/index.rst
@@ -12,6 +12,9 @@ You can use ROCm to perform distributed training, which enables you to train mod
 
 Overall, ROCm can be used to improve the performance and efficiency of your AI applications. With its training, fine-tuning, and inference support, ROCm provides a complete solution for optimizing AI workflows and achieving the optimum results possible on AMD GPUs. 

+The AI Developer Hub contains `AMD ROCm tutorials <https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/>`_ for
+training, fine-tuning, and inference. It leverages popular machine learning frameworks on AMD GPUs.
+
 In this guide, you'll learn how to use ROCm for AI:

 - :doc:`Training <training/index>`
--- a/docs/how-to/rocm-for-ai/inference-optimization/model-acceleration-libraries.rst
+++ b/docs/how-to/rocm-for-ai/inference-optimization/model-acceleration-libraries.rst
@@ -277,7 +277,7 @@ Installing FBGEMM_GPU
 Installing FBGEMM_GPU consists of the following steps:

 *  Set up an isolated Miniconda environment
-*  Install ROCm using Docker or the :doc:`package manager <rocm-install-on-linux:install/native-install/index>`
+*  Install ROCm using Docker or the :doc:`package manager <rocm-install-on-linux:install/install-methods/package-manager-index>`
 *  Install the nightly `PyTorch <https://pytorch.org/>`_ build
 *  Complete the pre-build and build tasks
  
--- a/docs/how-to/rocm-for-ai/inference/index.rst
+++ b/docs/how-to/rocm-for-ai/inference/index.rst
@@ -11,6 +11,9 @@ Understanding the ROCm™ software platform’s architecture and capabilities is

 Throughout the following topics, this section provides a comprehensive guide to setting up and deploying AI inference on AMD GPUs. This includes instructions on how to install ROCm, how to use Hugging Face Transformers to manage pre-trained models for natural language processing (NLP) tasks, how to validate vLLM on AMD Instinct™ MI300X accelerators and illustrate how to deploy trained models in production environments. 

+The AI Developer Hub contains `AMD ROCm tutorials <https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/>`_ for
+training, fine-tuning, and inference. It leverages popular machine learning frameworks on AMD GPUs.
+
 - :doc:`Installing ROCm and machine learning frameworks <install>`

 - :doc:`Running models from Hugging Face <hugging-face-models>`
--- a/docs/how-to/rocm-for-ai/inference/install.rst
+++ b/docs/how-to/rocm-for-ai/inference/install.rst
@@ -26,7 +26,7 @@ If you’re using a Radeon GPU for graphics-accelerated applications, refer to t

 ROCm supports multiple :doc:`installation methods <rocm-install-on-linux:install/install-overview>`:

-* :doc:`Using your Linux distribution's package manager <rocm-install-on-linux:install/native-install/index>`
+* :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/amdgpu-install>`

--- a/docs/how-to/rocm-for-ai/inference/vllm-benchmark.rst
+++ b/docs/how-to/rocm-for-ai/inference/vllm-benchmark.rst
@@ -10,49 +10,22 @@ LLM inference performance validation on AMD Instinct MI300X
 .. _vllm-benchmark-unified-docker:

 The `ROCm vLLM Docker <https://hub.docker.com/r/rocm/vllm/tags>`_ image offers
-a prebuilt, optimized environment designed for validating large language model
-(LLM) inference performance on the AMD Instinct™ MI300X accelerator. This
-ROCm vLLM Docker image integrates vLLM and PyTorch tailored specifically for the
-MI300X accelerator and includes the following components:
+a prebuilt, optimized environment for validating large language model (LLM)
+inference performance on the AMD Instinct™ MI300X accelerator. This ROCm vLLM
+Docker image integrates vLLM and PyTorch tailored specifically for the MI300X
+accelerator and includes the following components:

-* `ROCm 6.2.1 <https://github.com/ROCm/ROCm>`_
+* `ROCm 6.3.1 <https://github.com/ROCm/ROCm>`_

-* `vLLM 0.6.4 <https://docs.vllm.ai/en/latest>`_
+* `vLLM 0.6.6 <https://docs.vllm.ai/en/latest>`_

-* `PyTorch 2.5.0 <https://github.com/pytorch/pytorch>`_
-
-* Tuning files (in CSV format)
+* `PyTorch 2.7.0 (2.7.0a0+git3a58512) <https://github.com/pytorch/pytorch>`_

 With this Docker image, you can quickly validate the expected inference
-performance numbers on the MI300X accelerator. This topic also provides tips on
-optimizing performance with popular AI models.
-
-.. hlist::
-   :columns: 6
-
-   * Llama 3.1 8B
-
-   * Llama 3.1 70B
-
-   * Llama 3.1 405B
-
-   * Llama 2 7B
-
-   * Llama 2 70B
-
-   * Mixtral 8x7B
-
-   * Mixtral 8x22B
-
-   * Mixtral 7B
-
-   * Qwen2 7B
-
-   * Qwen2 72B
-
-   * JAIS 13B
-
-   * JAIS 30B
+performance numbers for the MI300X accelerator. This topic also provides tips on
+optimizing performance with popular AI models. For more information, see the lists of
+:ref:`available models for MAD-integrated benchmarking <vllm-benchmark-mad-models>`
+and :ref:`standalone benchmarking <vllm-benchmark-standalone-options>`.

 .. _vllm-benchmark-vllm:

@@ -91,9 +64,9 @@ MI300X accelerator with the prebuilt vLLM Docker image.

   .. code-block:: shell

-      docker pull rocm/vllm:rocm6.2_mi300_ubuntu20.04_py3.9_vllm_0.6.4
+      docker pull rocm/vllm:rocm6.3.1_mi300_ubuntu22.04_py3.12_vllm_0.6.6

-Once setup is complete, you can choose between two options to reproduce the
+Once the setup is complete, choose between two options to reproduce the
 benchmark results:

 -  :ref:`MAD-integrated benchmarking <vllm-benchmark-mad>`
@@ -130,45 +103,89 @@ Although the following models are preconfigured to collect latency and
 throughput performance data, you can also change the benchmarking parameters.
 Refer to the :ref:`Standalone benchmarking <vllm-benchmark-standalone>` section.

+.. _vllm-benchmark-mad-models:
+
 Available models
 ----------------

-.. hlist::
-   :columns: 3
+.. list-table::
+   :header-rows: 1
+   :widths: 2, 3

-   * ``pyt_vllm_llama-3.1-8b``
+   * - Model name
+     - Tag

-   * ``pyt_vllm_llama-3.1-70b``
+   * - `Llama 3.1 8B <https://huggingface.co/meta-llama/Llama-3.1-8B>`_
+     - ``pyt_vllm_llama-3.1-8b``

-   * ``pyt_vllm_llama-3.1-405b``
+   * - `Llama 3.1 70B <https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct>`_
+     - ``pyt_vllm_llama-3.1-70b``

-   * ``pyt_vllm_llama-2-7b``
+   * - `Llama 3.1 405B <https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct>`_
+     - ``pyt_vllm_llama-3.1-405b``

-   * ``pyt_vllm_llama-2-70b``
+   * - `Llama 3.2 11B Vision <https://huggingface.co/meta-llama/Llama-3.2-11B-Vision-Instruct>`_
+     - ``pyt_vllm_llama-3.2-11b-vision-instruct``

-   * ``pyt_vllm_mixtral-8x7b``
+   * - `Llama 2 7B <https://huggingface.co/meta-llama/Llama-2-7b-chat-hf>`_
+     - ``pyt_vllm_llama-2-7b``

-   * ``pyt_vllm_mixtral-8x22b``
+   * - `Llama 2 70B <https://huggingface.co/meta-llama/Llama-2-70b-chat-hf>`_
+     - ``pyt_vllm_llama-2-70b``

-   * ``pyt_vllm_mistral-7b``
+   * - `Mixtral MoE 8x7B <https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1>`_
+     - ``pyt_vllm_mixtral-8x7b``

-   * ``pyt_vllm_qwen2-7b``
+   * - `Mixtral MoE 8x22B <https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1>`_
+     - ``pyt_vllm_mixtral-8x22b``

-   * ``pyt_vllm_qwen2-72b``
+   * - `Mistral 7B <https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3>`_
+     - ``pyt_vllm_mistral-7b``

-   * ``pyt_vllm_jais-13b``
+   * - `Qwen2 7B <https://huggingface.co/Qwen/Qwen2-7B-Instruct>`_
+     - ``pyt_vllm_qwen2-7b``

-   * ``pyt_vllm_jais-30b``
+   * - `Qwen2 72B <https://huggingface.co/Qwen/Qwen2-72B-Instruct>`_
+     - ``pyt_vllm_qwen2-72b``

-   * ``pyt_vllm_llama-3.1-8b_fp8``
+   * - `JAIS 13B <https://huggingface.co/core42/jais-13b-chat>`_
+     - ``pyt_vllm_jais-13b``

-   * ``pyt_vllm_llama-3.1-70b_fp8``
+   * - `JAIS 30B <https://huggingface.co/core42/jais-30b-chat-v3>`_
+     - ``pyt_vllm_jais-30b``

-   * ``pyt_vllm_llama-3.1-405b_fp8``
+   * - `DBRX Instruct <https://huggingface.co/databricks/dbrx-instruct>`_
+     - ``pyt_vllm_dbrx-instruct``

-   * ``pyt_vllm_mixtral-8x7b_fp8``
+   * - `Gemma 2 27B <https://huggingface.co/google/gemma-2-27b>`_
+     - ``pyt_vllm_gemma-2-27b``

-   * ``pyt_vllm_mixtral-8x22b_fp8``
+   * - `C4AI Command R+ 08-2024 <https://huggingface.co/CohereForAI/c4ai-command-r-plus-08-2024>`_
+     - ``pyt_vllm_c4ai-command-r-plus-08-2024``
+
+   * - `DeepSeek MoE 16B <https://huggingface.co/deepseek-ai/deepseek-moe-16b-chat>`_
+     - ``pyt_vllm_deepseek-moe-16b-chat``
+
+   * - `Llama 3.1 70B FP8 <https://huggingface.co/amd/Llama-3.1-70B-Instruct-FP8-KV>`_
+     - ``pyt_vllm_llama-3.1-70b_fp8``
+
+   * - `Llama 3.1 405B FP8 <https://huggingface.co/amd/Llama-3.1-405B-Instruct-FP8-KV>`_
+     - ``pyt_vllm_llama-3.1-405b_fp8``
+
+   * - `Mixtral MoE 8x7B FP8 <https://huggingface.co/amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV>`_
+     - ``pyt_vllm_mixtral-8x7b_fp8``
+
+   * - `Mixtral MoE 8x22B FP8 <https://huggingface.co/amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV>`_
+     - ``pyt_vllm_mixtral-8x22b_fp8``
+
+   * - `Mistral 7B FP8 <https://huggingface.co/amd/Mistral-7B-v0.1-FP8-KV>`_
+     - ``pyt_vllm_mistral-7b_fp8``
+
+   * - `DBRX Instruct FP8 <https://huggingface.co/amd/dbrx-instruct-FP8-KV>`_
+     - ``pyt_vllm_dbrx_fp8``
+
+   * - `C4AI Command R+ 08-2024 FP8 <https://huggingface.co/amd/c4ai-command-r-plus-FP8-KV>`_
+     - ``pyt_vllm_command-r-plus_fp8``

 .. _vllm-benchmark-standalone:

@@ -181,8 +198,8 @@ snippet.

 .. code-block::

-   docker pull rocm/vllm:rocm6.2_mi300_ubuntu20.04_py3.9_vllm_0.6.4
-   docker run -it --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128G --security-opt seccomp=unconfined --security-opt apparmor=unconfined --cap-add=SYS_PTRACE -v $(pwd):/workspace --env HUGGINGFACE_HUB_CACHE=/workspace --name vllm_v0.6.4 rocm/vllm:rocm6.2_mi300_ubuntu20.04_py3.9_vllm_0.6.4
+   docker pull rocm/vllm:rocm6.3.1_mi300_ubuntu22.04_py3.12_vllm_0.6.6
+   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 vllm_v0.6.6 rocm/vllm:rocm6.3.1_mi300_ubuntu22.04_py3.12_vllm_0.6.6

 In the Docker container, clone the ROCm MAD repository and navigate to the
 benchmark scripts directory at ``~/MAD/scripts/vllm``.
@@ -224,8 +241,8 @@ See the :ref:`examples <vllm-benchmark-run-benchmark>` for more information.

 .. _vllm-benchmark-standalone-options:

-Options
-------
+Options and available models
+----------------------------

 .. list-table::
   :header-rows: 1
@@ -248,72 +265,100 @@ Options
     - Measure both throughput and latency

   * - ``$model_repo``
-     - ``meta-llama/Meta-Llama-3.1-8B-Instruct``
-     - Llama 3.1 8B
+     - ``meta-llama/Llama-3.1-8B-Instruct``
+     - `Llama 3.1 8B <https://huggingface.co/meta-llama/Llama-3.1-8B>`_

   * - (``float16``)
-     - ``meta-llama/Meta-Llama-3.1-70B-Instruct``
-     - Llama 3.1 70B
+     - ``meta-llama/Llama-3.1-70B-Instruct``
+     - `Llama 3.1 70B <https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct>`_

   * -
-     - ``meta-llama/Meta-Llama-3.1-405B-Instruct``
-     - Llama 3.1 405B
+     - ``meta-llama/Llama-3.1-405B-Instruct``
+     - `Llama 3.1 405B <https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct>`_
+
+   * -
+     - ``meta-llama/Llama-3.2-11B-Vision-Instruct``
+     - `Llama 3.2 11B Vision <https://huggingface.co/meta-llama/Llama-3.2-11B-Vision-Instruct>`_

   * -
     - ``meta-llama/Llama-2-7b-chat-hf``
-     - Llama 2 7B
+     - `Llama 2 7B <https://huggingface.co/meta-llama/Llama-2-7b-chat-hf>`_

   * -
     - ``meta-llama/Llama-2-70b-chat-hf``
-     - Llama 2 70B
+     - `Llama 2 7B <https://huggingface.co/meta-llama/Llama-2-70b-chat-hf>`_

   * -
     - ``mistralai/Mixtral-8x7B-Instruct-v0.1``
-     - Mixtral 8x7B
+     - `Mixtral MoE 8x7B <https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1>`_

   * -
     - ``mistralai/Mixtral-8x22B-Instruct-v0.1``
-     - Mixtral 8x22B
+     - `Mixtral MoE 8x22B <https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1>`_

   * -
     - ``mistralai/Mistral-7B-Instruct-v0.3``
-     - Mixtral 7B
+     - `Mistral 7B <https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3>`_

   * -
     - ``Qwen/Qwen2-7B-Instruct``
-     - Qwen2 7B
+     - `Qwen2 7B <https://huggingface.co/Qwen/Qwen2-7B-Instruct>`_

   * -
     - ``Qwen/Qwen2-72B-Instruct``
-     - Qwen2 72B
+     - `Qwen2 72B <https://huggingface.co/Qwen/Qwen2-72B-Instruct>`_

   * -
     - ``core42/jais-13b-chat``
-     - JAIS 13B
+     - `JAIS 13B <https://huggingface.co/core42/jais-13b-chat>`_

   * -
     - ``core42/jais-30b-chat-v3``
-     - JAIS 30B
-
-   * - ``$model_repo``
-     - ``amd/Meta-Llama-3.1-8B-Instruct-FP8-KV``
-     - Llama 3.1 8B
-
-   * - (``float8``)
-     - ``amd/Meta-Llama-3.1-70B-Instruct-FP8-KV``
-     - Llama 3.1 70B
+     - `JAIS 30B <https://huggingface.co/core42/jais-30b-chat-v3>`_

   * -
-     - ``amd/Meta-Llama-3.1-405B-Instruct-FP8-KV``
-     - Llama 3.1 405B
+     - ``databricks/dbrx-instruct``
+     - `DBRX Instruct <https://huggingface.co/databricks/dbrx-instruct>`_
+
+   * -
+     - ``google/gemma-2-27b``
+     - `Gemma 2 27B <https://huggingface.co/google/gemma-2-27b>`_
+
+   * -
+     - ``CohereForAI/c4ai-command-r-plus-08-2024``
+     - `C4AI Command R+ 08-2024 <https://huggingface.co/CohereForAI/c4ai-command-r-plus-08-2024>`_
+
+   * -
+     - ``deepseek-ai/deepseek-moe-16b-chat``
+     - `DeepSeek MoE 16B <https://huggingface.co/deepseek-ai/deepseek-moe-16b-chat>`_
+
+   * - ``$model_repo``
+     - ``amd/Llama-3.1-70B-Instruct-FP8-KV``
+     - `Llama 3.1 70B FP8 <https://huggingface.co/amd/Llama-3.1-70B-Instruct-FP8-KV>`_
+
+   * - (``float8``)
+     - ``amd/Llama-3.1-405B-Instruct-FP8-KV``
+     - `Llama 3.1 405B FP8 <https://huggingface.co/amd/Llama-3.1-405B-Instruct-FP8-KV>`_

   * -
     - ``amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV``
-     - Mixtral 8x7B
+     - `Mixtral MoE 8x7B FP8 <https://huggingface.co/amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV>`_

   * -
     - ``amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV``
-     - Mixtral 8x22B
+     - `Mixtral MoE 8x22B FP8 <https://huggingface.co/amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV>`_
+
+   * -
+     - ``amd/Mistral-7B-v0.1-FP8-KV``
+     - `Mistral 7B FP8 <https://huggingface.co/amd/Mistral-7B-v0.1-FP8-KV>`_
+
+   * -
+     - ``amd/dbrx-instruct-FP8-KV``
+     - `DBRX Instruct FP8 <https://huggingface.co/amd/dbrx-instruct-FP8-KV>`_
+
+   * -
+     - ``amd/c4ai-command-r-plus-FP8-KV``
+     - `C4AI Command R+ 08-2024 FP8 <https://huggingface.co/amd/c4ai-command-r-plus-FP8-KV>`_

   * - ``$num_gpu``
     - 1 or 8
@@ -335,34 +380,34 @@ options and their descriptions.
 Example 1: latency benchmark
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Use this command to benchmark the latency of the Llama 3.1 8B model on one GPU with the ``float16`` and ``float8`` data types.
+Use this command to benchmark the latency of the Llama 3.1 70B model on eight GPUs with the ``float16`` and ``float8`` data types.

 .. code-block::

-   ./vllm_benchmark_report.sh -s latency -m meta-llama/Meta-Llama-3.1-8B-Instruct -g 1 -d float16
-   ./vllm_benchmark_report.sh -s latency -m amd/Meta-Llama-3.1-8B-Instruct-FP8-KV -g 1 -d float8
+   ./vllm_benchmark_report.sh -s latency -m meta-llama/Llama-3.1-70B-Instruct -g 8 -d float16
+   ./vllm_benchmark_report.sh -s latency -m amd/Llama-3.1-70B-Instruct-FP8-KV -g 8 -d float8

 Find the latency reports at:

- ``./reports_float16/summary/Meta-Llama-3.1-8B-Instruct_latency_report.csv``
+- ``./reports_float16/summary/Llama-3.1-70B-Instruct_latency_report.csv``

- ``./reports_float8/summary/Meta-Llama-3.1-8B-Instruct-FP8-KV_latency_report.csv``
+- ``./reports_float8/summary/Llama-3.1-70B-Instruct-FP8-KV_latency_report.csv``

 Example 2: throughput benchmark
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

-Use this command to benchmark the throughput of the Llama 3.1 8B model on one GPU with the ``float16`` and ``float8`` data types.
+Use this command to benchmark the throughput of the Llama 3.1 70B model on eight GPUs with the ``float16`` and ``float8`` data types.

 .. code-block:: shell

-   ./vllm_benchmark_report.sh -s throughput -m meta-llama/Meta-Llama-3.1-8B-Instruct -g 1 -d float16
-   ./vllm_benchmark_report.sh -s throughput -m amd/Meta-Llama-3.1-8B-Instruct-FP8-KV -g 1 -d float8
+   ./vllm_benchmark_report.sh -s throughput -m meta-llama/Llama-3.1-70B-Instruct -g 8 -d float16
+   ./vllm_benchmark_report.sh -s throughput -m amd/Llama-3.1-70B-Instruct-FP8-KV -g 8 -d float8

 Find the throughput reports at:

- ``./reports_float16/summary/Meta-Llama-3.1-8B-Instruct_throughput_report.csv``
+- ``./reports_float16/summary/Llama-3.1-70B-Instruct_throughput_report.csv``

- ``./reports_float8/summary/Meta-Llama-3.1-8B-Instruct-FP8-KV_throughput_report.csv``
+- ``./reports_float8/summary/Llama-3.1-70B-Instruct-FP8-KV_throughput_report.csv``

 .. raw:: html

@@ -394,7 +439,7 @@ Further reading
  MI300X accelerators, see :doc:`../../system-optimization/mi300x`.

 - To learn how to run LLM models from Hugging Face or your own model, see
-  :doc:`Using ROCm for AI <../index>`.
+  :doc:`Running models from Hugging Face <hugging-face-models>`.

 - To learn how to optimize inference on LLMs, see
  :doc:`Inference optimization <../inference-optimization/index>`.
@@ -402,6 +447,32 @@ Further reading
 - To learn how to fine-tune LLMs, see
  :doc:`Fine-tuning LLMs <../fine-tuning/index>`.

- To compare with the previous version of the ROCm vLLM Docker image for performance validation, refer to
-  `LLM inference performance validation on AMD Instinct MI300X (ROCm 6.2.0) <https://rocm.docs.amd.com/en/docs-6.2.0/how-to/performance-validation/mi300x/vllm-benchmark.html>`_.
+Previous versions
+=================

+This table lists previous versions of the ROCm vLLM Docker image for inference
+performance validation. For detailed information about available models for
+benchmarking, see the version-specific documentation.
+
+.. list-table::
+   :header-rows: 1
+   :stub-columns: 1
+
+   * - ROCm version
+     - vLLM version
+     - PyTorch version
+     - Resources
+
+   * - 6.2.1
+     - 0.6.4
+     - 2.5.0
+     - 
+       * `Documentation <https://rocm.docs.amd.com/en/docs-6.3.0/how-to/performance-validation/mi300x/vllm-benchmark.html>`_
+       * `Docker Hub <https://hub.docker.com/layers/rocm/vllm/rocm6.2_mi300_ubuntu20.04_py3.9_vllm_0.6.4/images/sha256-ccbb74cc9e7adecb8f7bdab9555f7ac6fc73adb580836c2a35ca96ff471890d8>`_
+
+   * - 6.2.0
+     - 0.4.3
+     - 2.4.0
+     -
+       * `Documentation <https://rocm.docs.amd.com/en/docs-6.2.0/how-to/performance-validation/mi300x/vllm-benchmark.html>`_
+       * `Docker Hub <https://hub.docker.com/layers/rocm/vllm/rocm6.2_mi300_ubuntu22.04_py3.9_vllm_7c5fd50/images/sha256-9e4dd4788a794c3d346d7d0ba452ae5e92d39b8dfac438b2af8efdc7f15d22c0>`_
--- a/docs/how-to/rocm-for-ai/training/index.rst
+++ b/docs/how-to/rocm-for-ai/training/index.rst
@@ -14,6 +14,9 @@ Training models on AMD GPUs with the ROCm™ software platform allows you to use
 
 The ROCm software platform makes it easier to train models on AMD GPUs while maintaining compatibility with existing code and tools. The platform also provides features like multi-GPU support, allowing for scaling and parallelization of model training across multiple GPUs to enhance performance. 

+The AI Developer Hub contains `AMD ROCm tutorials <https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/>`_ for
+training, fine-tuning, and inference. It leverages popular machine learning frameworks on AMD GPUs.
+
 In this guide, you'll learn about:

 - :doc:`Training a model <train-a-model>`
--- a/docs/how-to/system-optimization/w6000-v620.md
+++ b/docs/how-to/system-optimization/w6000-v620.md
@@ -12,7 +12,7 @@ myst:
 This chapter reviews system settings that are required to configure the system
 for ROCm virtualization on RDNA2-based AMD Radeon™ PRO GPUs. Installing ROCm on
 Bare Metal follows the routine ROCm
-{doc}`installation procedure<rocm-install-on-linux:install/native-install/index>`.
+{doc}`installation procedure<rocm-install-on-linux:install/install-methods/package-manager-index>`.

 To enable ROCm virtualization on V620, one has to setup Single Root I/O
 Virtualization (SR-IOV) in the BIOS via setting found in the following
@@ -166,4 +166,4 @@ First, assign GPU virtual function (VF) to VM using the following steps.
 Then start the VM.

 Finally install ROCm on the virtual machine (VM). For detailed instructions,
-refer to the {doc}`Linux install guide<rocm-install-on-linux:install/native-install/index>`.
+refer to the {doc}`Linux install guide<rocm-install-on-linux:install/install-methods/package-manager-index>`.
--- a/docs/index.md
+++ b/docs/index.md
@@ -38,6 +38,7 @@ ROCm documentation is organized into the following categories:
 :class-body: rocm-card-banner rocm-hue-12

 * [Use ROCm for AI](./how-to/rocm-for-ai/index.rst)
+* [AI tutorials](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/)
 * [Use ROCm for HPC](./how-to/rocm-for-hpc/index.rst)
 * [System optimization](./how-to/system-optimization/index.rst)
 * [AMD Instinct MI300X performance validation and tuning](./how-to/tuning-guides/mi300x/index.rst)
--- a/docs/reference/gpu-arch-specs.rst
+++ b/docs/reference/gpu-arch-specs.rst
@@ -32,6 +32,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - L1 Instruction Cache (KiB)
          - VGPR File (KiB)
          - SGPR File (KiB)
+          - GFXIP Major version
+          - GFXIP Minor version
        *
          - MI325X
          - CDNA3
@@ -47,6 +49,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 64 per 2 CUs
          - 512
          - 12.5
+          - 9
+          - 4
        *
          - MI300X
          - CDNA3
@@ -62,6 +66,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 64 per 2 CUs
          - 512
          - 12.5
+          - 9
+          - 4
        *
          - MI300A
          - CDNA3
@@ -77,6 +83,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 64 per 2 CUs
          - 512
          - 12.5
+          - 9
+          - 4
        *
          - MI250X
          - CDNA2
@@ -92,6 +100,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 2 CUs
          - 512
          - 12.5
+          - 9
+          - 0
        *
          - MI250
          - CDNA2
@@ -107,6 +117,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 2 CUs
          - 512
          - 12.5
+          - 9
+          - 0
        *
          - MI210
          - CDNA2
@@ -122,6 +134,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 2 CUs
          - 512
          - 12.5
+          - 9
+          - 0
        *
          - MI100
          - CDNA
@@ -137,6 +151,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 3 CUs
          - 256 VGPR and 256 AccVGPR
          - 12.5
+          - 9
+          - 0
        *
          - MI60
          - GCN5.1
@@ -152,6 +168,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 3 CUs
          - 256
          - 12.5
+          - 9
+          - 0
        *
          - MI50 (32GB)
          - GCN5.1
@@ -167,6 +185,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 3 CUs
          - 256
          - 12.5
+          - 9
+          - 0
        *
          - MI50 (16GB)
          - GCN5.1
@@ -182,6 +202,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 3 CUs
          - 256
          - 12.5
+          - 9
+          - 0
        *
          - MI25
          - GCN5.0
@@ -197,6 +219,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 3 CUs
          - 256
          - 12.5
+          - 9
+          - 0
        *
          - MI8
          - GCN3.0
@@ -212,6 +236,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 4 CUs
          - 256
          - 12.5
+          - 8
+          - 0
        *
          - MI6
          - GCN4.0
@@ -227,6 +253,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 4 CUs
          - 256
          - 12.5
+          - 8
+          - 0

  .. tab-item:: AMD Radeon PRO GPUs

@@ -238,6 +266,7 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - Model
          - Architecture
          - LLVM target name
+
          - VRAM (GiB)
          - Compute Units
          - Wavefront Size
@@ -250,6 +279,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - L0 Instruction Cache (KiB)
          - VGPR File (KiB)
          - SGPR File (KiB)
+          - GFXIP Major version
+          - GFXIP Minor version
        *
          - Radeon PRO V710
          - RDNA3
@@ -266,6 +297,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon PRO W7900 Dual Slot
          - RDNA3
@@ -282,6 +315,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon PRO W7900
          - RDNA3
@@ -298,6 +333,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon PRO W7800
          - RDNA3
@@ -314,6 +351,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon PRO W7700
          - RDNA3
@@ -330,6 +369,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon PRO W6800
          - RDNA2
@@ -346,6 +387,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon PRO W6600
          - RDNA2
@@ -362,6 +405,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon PRO V620
          - RDNA2
@@ -378,6 +423,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon Pro W5500
          - RDNA
@@ -394,6 +441,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 20
+          - 10
+          - 1
        *
          - Radeon Pro VII
          - GCN5.1
@@ -410,6 +459,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 3 CUs
          - 256
          - 12.5
+          - 9
+          - 0

  .. tab-item:: AMD Radeon GPUs

@@ -433,6 +484,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - L0 Instruction Cache (KiB)
          - VGPR File (KiB)
          - SGPR File (KiB)
+          - GFXIP Major version
+          - GFXIP Minor version
        *
          - Radeon RX 7900 XTX
          - RDNA3
@@ -449,6 +502,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon RX 7900 XT
          - RDNA3
@@ -465,6 +520,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon RX 7900 GRE
          - RDNA3
@@ -481,6 +538,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon RX 7800 XT
          - RDNA3
@@ -497,6 +556,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon RX 7700 XT
          - RDNA3
@@ -513,6 +574,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 768
          - 16
+          - 11
+          - 0
        *
          - Radeon RX 7600
          - RDNA3
@@ -529,6 +592,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 11
+          - 0
        *
          - Radeon RX 6950 XT
          - RDNA2
@@ -545,6 +610,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6900 XT
          - RDNA2
@@ -561,6 +628,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6800 XT
          - RDNA2
@@ -577,6 +646,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6800
          - RDNA2
@@ -593,6 +664,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6750 XT
          - RDNA2
@@ -609,6 +682,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6700 XT
          - RDNA2
@@ -625,6 +700,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6700
          - RDNA2
@@ -641,6 +718,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6650 XT
          - RDNA2
@@ -657,6 +736,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6600 XT
          - RDNA2
@@ -673,6 +754,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon RX 6600
          - RDNA2
@@ -689,6 +772,8 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32
          - 512
          - 16
+          - 10
+          - 3
        *
          - Radeon VII
          - GCN5.1
@@ -705,12 +790,14 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
          - 32 per 3 CUs
          - 256
          - 12.5
+          - 9
+          - 0

 Glossary
 ========

 For more information about the terms used, see the
-:ref:`specific documents and guides <gpu-arch-documentation>`, or 
+:ref:`specific documents and guides <gpu-arch-documentation>`, or
 :doc:`Understanding the HIP programming model<hip:understand/programming_model>`.

 **LLVM target name**
@@ -800,6 +887,26 @@ Purpose Vector Registers, used specifically in matrix instructions.
 Size of the Scalar General Purpose Register (SGPR) file. Holds data used in
 scalar instructions.

+**GFXIP**
+
+GFXIP (Graphics IP) is a versioning system used by AMD to identify the GPU
+architecture and its instruction set. It helps categorize different generations
+of GPUs and their feature sets.
+
+**GFXIP major version**
+
+Defines the GPU's core instruction set and architecture, which determines
+compatibility with software stacks such as HIP and OpenCL. For example, a GFXIP
+11 major version corresponds to the RDNA 3 (Navi 3x) architecture, influencing
+driver support and available compute features.
+
+**GFXIP minor version**
+
+Represents specific variations within a GFXIP major version and affects feature sets,
+optimizations, and driver behavior in software stacks such as HIP and OpenCL. Different
+GPU models within the same major version can have unique capabilities, impacting
+performance and supported instructions.
+
 **GCD**

 Graphics Compute Die.
--- a/docs/reference/precision-support.rst
+++ b/docs/reference/precision-support.rst
@@ -1,19 +1,23 @@
 .. meta::
-  :description: Supported data types in ROCm
-  :keywords: int8, float8, float8 (E4M3), float8 (E5M2), bfloat8, float16, half, bfloat16, tensorfloat32, float,
-   float32, float64, double, AMD, ROCm, AMDGPU
+  :description: Supported data types of AMD GPUs and libraries in ROCm.
+  :keywords: precision, data types, HIP types, int8, float8, float8 (E4M3),
+             float8 (E5M2), bfloat8, float16, half, bfloat16, tensorfloat32,
+             float, float32, float64, double, AMD data types, HIP data types,
+             ROCm precision, ROCm data types

 *************************************************************
-Precision support
+Data types and precision support
 *************************************************************

-Use the following sections to identify data types and HIP types ROCm™ supports.
+This topic lists the supported data types of AMD GPUs and ROCm libraries.
+Corresponding :doc:`HIP <hip:index>` data types are also noted. 

 Integral types
 ==========================================

-The signed and unsigned integral types that are supported by ROCm are listed in the following table,
-together with their corresponding HIP type and a short description.
+The signed and unsigned integral types supported by ROCm are listed in
+the following table, along with their corresponding HIP type and a short
+description.


 .. list-table::
@@ -46,8 +50,8 @@ together with their corresponding HIP type and a short description.
 Floating-point types
 ==========================================

-The floating-point types that are supported by ROCm are listed in the following table, together with
-their corresponding HIP type and a short description.
+The floating-point types supported by ROCm are listed in the following
+table, along with their corresponding HIP type and a short description.

 .. image:: ../data/about/compatibility/floating-point-data-types.png
    :alt: Supported floating-point types
@@ -63,43 +67,62 @@ their corresponding HIP type and a short description.
    *
      - float8 (E4M3)
      - ``-``
-      - 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 with no infinity or signed zero. NaN is represented as negative zero.
+      - 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.
    *
      - float8 (E5M2)
      - ``-``
-      - 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 with no infinity or signed zero. NaN is represented as negative zero.
+      - 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.
    *
      - float16
      - ``half``
-      - A 16-bit floating-point number that conforms to the IEEE 754-2008 half-precision storage format.
+      - A 16-bit floating-point number that conforms to the IEEE 754-2008
+        half-precision storage format.
    *
      - bfloat16
      - ``bfloat16``
-      - A shortened 16-bit version of the IEEE 754 single-precision storage format.
+      - A shortened 16-bit version of the IEEE 754 single-precision storage
+        format.
    *
      - tensorfloat32
      - ``-``
-      - A floating-point number that occupies 32 bits or less of storage, providing improved range compared to half (16-bit) format, at (potentially) greater throughput than single-precision (32-bit) formats.
+      - A floating-point number that occupies 32 bits or less of storage,
+        providing improved range compared to half (16-bit) format, at
+        (potentially) greater throughput than single-precision (32-bit) formats.
    *
      - float32
      - ``float``
-      - A 32-bit floating-point number that conforms to the IEEE 754 single-precision storage format.
+      - A 32-bit floating-point number that conforms to the IEEE 754
+        single-precision storage format.
    *
      - float64
      - ``double``
-      - A 64-bit floating-point number that conforms to the IEEE 754 double-precision storage format.
+      - A 64-bit floating-point number that conforms to the IEEE 754
+        double-precision storage format.

 .. note::

-  * 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 are natively supported by MI300 differ from the FP8 (E5M2) and FP8 (E4M3) encodings used in H100 (`FP8 Formats for Deep Learning <https://arxiv.org/abs/2209.05433>`_).
+  * 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
+    (`FP8 Formats for Deep Learning <https://arxiv.org/abs/2209.05433>`_).
+
  * In some AMD documents and articles, float8 (E5M2) is referred to as bfloat8.

 ROCm support icons
 ==========================================

-In the following sections, we use icons to represent the level of support. These icons, described in the
-following table, are also used on the library data type support pages.
+In the following sections, icons represent the level of support. These
+icons, described in the following table, are also used in the library data type
+support pages.

 .. list-table::
    :header-rows: 1
@@ -121,14 +144,27 @@ following table, are also used on the library data type support pages.

 .. note::

-  * Full support means that the type is supported natively or with hardware emulation.
-  * Native support means that the operations for that type are implemented in hardware. Types that are not natively supported are emulated with the available hardware. The performance of non-natively supported types can differ from the full instruction throughput rate. For example, 16-bit integer operations can be performed on the 32-bit integer ALUs at full rate; however, 64-bit integer operations might need several instructions on the 32-bit integer ALUs.
-  * Any type can be emulated by software, but this page does not cover such cases.
+  * Full support means that the type is supported natively or with hardware
+    emulation.

-Hardware type support
+  * Native support means that the operations for that type are implemented in
+    hardware. Types that are not natively supported are emulated with the
+    available hardware. The performance of non-natively supported types can
+    differ from the full instruction throughput rate. For example, 16-bit
+    integer operations can be performed on the 32-bit integer ALUs at full rate;
+    however, 64-bit integer operations might need several instructions on the
+    32-bit integer ALUs.
+
+  * Any type can be emulated by software, but this page does not cover such
+    cases.
+
+Hardware data type support
 ==========================================

-AMD GPU hardware support for data types is listed in the following tables.
+The following tables provide information about AMD Instinct accelerators support
+for various data types. 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 built on the CDNA3 architecture.

 Compute units support
 -------------------------------------------------------------------------------
@@ -375,21 +411,23 @@ The following table lists data type support for atomic operations.

 .. note::

-  For cases that are not natively supported, you can emulate atomic operations using software.
-  Software-emulated atomic operations have high negative performance impact when they frequently
-  access the same memory address.
+  You can emulate atomic operations using software for cases that are not
+  natively supported. Software-emulated atomic operations have a high negative
+  performance impact when they frequently access the same memory address.

-Data Type support in ROCm Libraries
+Data type support in ROCm libraries
 ==========================================

-ROCm library support for int8, float8 (E4M3), float8 (E5M2), int16, float16, bfloat16, int32,
-tensorfloat32, float32, int64, and float64 is listed in the following tables.
+ROCm library support for int8, float8 (E4M3), float8 (E5M2), int16, float16,
+bfloat16, int32, tensorfloat32, float32, int64, and float64 is listed in the
+following tables.

 Libraries input/output type support
 -------------------------------------------------------------------------------

-The following tables list ROCm library support for specific input and output data types. For a detailed
-description, refer to the corresponding library data type support page.
+The following tables list ROCm library support for specific input and output
+data types. Refer to the corresponding library data type support page for a
+detailed description.

 .. tab-set::

@@ -516,8 +554,9 @@ description, refer to the corresponding library data type support page.
 Libraries internal calculations type support
 -------------------------------------------------------------------------------

-The following tables list ROCm library support for specific internal data types. For a detailed
-description, refer to the corresponding library data type support page.
+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.

 .. tab-set::

--- a/docs/sphinx/_toc.yml.in
+++ b/docs/sphinx/_toc.yml.in
@@ -89,7 +89,10 @@ subtrees:
            title: Profile and debug
          - file: how-to/rocm-for-ai/inference-optimization/workload.rst
            title: Workload tuning
-  
+
+      - url: https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/
+        title: AI tutorials
+
  - file: how-to/rocm-for-hpc/index.rst
    title: Use ROCm for HPC
  - file: how-to/system-optimization/index.rst
@@ -126,6 +129,7 @@ subtrees:
  - url: https://github.com/amd/rocm-examples
    title: ROCm examples

+
 - caption: Conceptual
  entries:
  - file: conceptual/gpu-arch.md
--- a/docs/sphinx/requirements.in
+++ b/docs/sphinx/requirements.in
@@ -1,3 +1,3 @@
-rocm-docs-core==1.13.0
+rocm-docs-core==1.15.0
 sphinx-reredirects
 sphinx-sitemap
--- a/docs/sphinx/requirements.txt
+++ b/docs/sphinx/requirements.txt
@@ -8,6 +8,13 @@ accessible-pygments==0.0.5
    # via pydata-sphinx-theme
 alabaster==1.0.0
    # via sphinx
+asttokens==3.0.0
+    # via stack-data
+attrs==25.1.0
+    # via
+    #   jsonschema
+    #   jupyter-cache
+    #   referencing
 babel==2.16.0
    # via
    #   pydata-sphinx-theme
@@ -25,9 +32,17 @@ cffi==1.17.1
 charset-normalizer==3.4.0
    # via requests
 click==8.1.7
-    # via sphinx-external-toc
-cryptography==43.0.3
+    # via
+    #   jupyter-cache
+    #   sphinx-external-toc
+comm==0.2.2
+    # via ipykernel
+cryptography==44.0.1
    # via pyjwt
+debugpy==1.8.12
+    # via ipykernel
+decorator==5.1.1
+    # via ipython
 deprecated==1.2.15
    # via pygithub
 docutils==0.21.2
@@ -36,34 +51,103 @@ docutils==0.21.2
    #   myst-parser
    #   pydata-sphinx-theme
    #   sphinx
+exceptiongroup==1.2.2
+    # via ipython
+executing==2.2.0
+    # via stack-data
 fastjsonschema==2.20.0
-    # via rocm-docs-core
+    # via
+    #   nbformat
+    #   rocm-docs-core
 gitdb==4.0.11
    # via gitpython
 gitpython==3.1.43
    # via rocm-docs-core
+greenlet==3.1.1
+    # via sqlalchemy
 idna==3.10
    # via requests
 imagesize==1.4.1
    # via sphinx
+importlib-metadata==8.6.1
+    # via
+    #   jupyter-cache
+    #   myst-nb
+ipykernel==6.29.5
+    # via myst-nb
+ipython==8.31.0
+    # via
+    #   ipykernel
+    #   myst-nb
+jedi==0.19.2
+    # via ipython
 jinja2==3.1.5
    # via
    #   myst-parser
    #   sphinx
+jsonschema==4.23.0
+    # via nbformat
+jsonschema-specifications==2024.10.1
+    # via jsonschema
+jupyter-cache==1.0.1
+    # via myst-nb
+jupyter-client==8.6.3
+    # via
+    #   ipykernel
+    #   nbclient
+jupyter-core==5.7.2
+    # via
+    #   ipykernel
+    #   jupyter-client
+    #   nbclient
+    #   nbformat
 markdown-it-py==3.0.0
    # via
    #   mdit-py-plugins
    #   myst-parser
 markupsafe==3.0.2
    # via jinja2
+matplotlib-inline==0.1.7
+    # via
+    #   ipykernel
+    #   ipython
 mdit-py-plugins==0.4.2
    # via myst-parser
 mdurl==0.1.2
    # via markdown-it-py
-myst-parser==4.0.0
+myst-nb==1.1.2
    # via rocm-docs-core
+myst-parser==4.0.0
+    # via myst-nb
+nbclient==0.10.2
+    # via
+    #   jupyter-cache
+    #   myst-nb
+nbformat==5.10.4
+    # via
+    #   jupyter-cache
+    #   myst-nb
+    #   nbclient
+nest-asyncio==1.6.0
+    # via ipykernel
 packaging==24.2
-    # via sphinx
+    # via
+    #   ipykernel
+    #   sphinx
+parso==0.8.4
+    # via jedi
+pexpect==4.9.0
+    # via ipython
+platformdirs==4.3.6
+    # via jupyter-core
+prompt-toolkit==3.0.50
+    # via ipython
+psutil==6.1.1
+    # via ipykernel
+ptyprocess==0.7.0
+    # via pexpect
+pure-eval==0.2.3
+    # via stack-data
 pycparser==2.22
    # via cffi
 pydata-sphinx-theme==0.16.0
@@ -75,23 +159,42 @@ pygithub==2.5.0
 pygments==2.18.0
    # via
    #   accessible-pygments
+    #   ipython
    #   pydata-sphinx-theme
    #   sphinx
 pyjwt[crypto]==2.10.0
    # via pygithub
 pynacl==1.5.0
    # via pygithub
+python-dateutil==2.9.0.post0
+    # via jupyter-client
 pyyaml==6.0.2
    # via
+    #   jupyter-cache
+    #   myst-nb
    #   myst-parser
    #   rocm-docs-core
    #   sphinx-external-toc
+pyzmq==26.2.0
+    # via
+    #   ipykernel
+    #   jupyter-client
+referencing==0.36.2
+    # via
+    #   jsonschema
+    #   jsonschema-specifications
 requests==2.32.3
    # via
    #   pygithub
    #   sphinx
-rocm-docs-core==1.13.0
+rocm-docs-core==1.15.0
    # via -r requirements.in
+rpds-py==0.22.3
+    # via
+    #   jsonschema
+    #   referencing
+six==1.17.0
+    # via python-dateutil
 smmap==5.0.1
    # via gitdb
 snowballstemmer==2.2.0
@@ -101,6 +204,7 @@ soupsieve==2.6
 sphinx==8.1.3
    # via
    #   breathe
+    #   myst-nb
    #   myst-parser
    #   pydata-sphinx-theme
    #   rocm-docs-core
@@ -137,15 +241,43 @@ sphinxcontrib-qthelp==2.0.0
    # via sphinx
 sphinxcontrib-serializinghtml==2.0.0
    # via sphinx
+sqlalchemy==2.0.37
+    # via jupyter-cache
+stack-data==0.6.3
+    # via ipython
+tabulate==0.9.0
+    # via jupyter-cache
 tomli==2.1.0
    # via sphinx
+tornado==6.4.2
+    # via
+    #   ipykernel
+    #   jupyter-client
+traitlets==5.14.3
+    # via
+    #   comm
+    #   ipykernel
+    #   ipython
+    #   jupyter-client
+    #   jupyter-core
+    #   matplotlib-inline
+    #   nbclient
+    #   nbformat
 typing-extensions==4.12.2
    # via
+    #   ipython
+    #   myst-nb
    #   pydata-sphinx-theme
    #   pygithub
+    #   referencing
+    #   sqlalchemy
 urllib3==2.2.3
    # via
    #   pygithub
    #   requests
+wcwidth==0.2.13
+    # via prompt-toolkit
 wrapt==1.17.0
    # via deprecated
+zipp==3.21.0
+    # via importlib-metadata
Author	SHA1	Message	Date
Adel Johar	0c6f660d59	Docs: Fix gpu-arch-spec.rst	2025-02-19 17:05:01 +01:00
Daniel Su	6cc343f180	Ex CI: set ROCM_PATH for MIOpen tests (#4371 )	2025-02-13 16:03:56 -05:00
Adel Johar	c52aa329c8	Merge pull request #4350 from ROCm/docs_device_version Docs: Add Device Major/Minor Versions to gpu-arch-spec.rst	2025-02-13 14:41:01 +01:00
Adel Johar	1499f74c22	Docs: Add Device Major/Minor Versions to gpu-arch-spec.rst	2025-02-13 14:24:00 +01:00
Daniel Su	a9aaabcc68	Ex CI: remove manual hipify-perl chmod from rccl (#4368 )	2025-02-12 11:36:53 -05:00
dependabot[bot]	24603ac37a	Build(deps): Bump cryptography from 43.0.3 to 44.0.1 in /docs/sphinx (#4365 ) Bumps [cryptography](https://github.com/pyca/cryptography) from 43.0.3 to 44.0.1. - [Changelog](https://github.com/pyca/cryptography/blob/main/CHANGELOG.rst) - [Commits](https://github.com/pyca/cryptography/compare/43.0.3...44.0.1) --- updated-dependencies: - dependency-name: cryptography dependency-type: indirect ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>	2025-02-11 17:01:16 -07:00
Joseph Macaranas	a6b1c656b0	External CI: Fix ROCR common test suite build (#4364 ) - Removing the creation of expected folders and symbolic links as workaround to get the test components compiling. - Set the only OpenCL build flag affecting the build.	2025-02-11 14:44:26 -05:00
Joseph Macaranas	82cf58912c	External CI: Fix failures for rocprofiler-systems and ROCR-Runtime (#4361 ) - Add rocm_smi_lib dependency to rocprofiler-systems. - Explicitly set OPENCL_INC_DIR in ROCR-Runtime test job.	2025-02-10 14:06:59 -05:00
Pratik Basyal	c469e34b27	Debian 12 support for single-node added (#300 ) (#4357 )	2025-02-10 09:33:27 -05:00
Joseph Macaranas	b6d19bd91c	External CI: rocWMMA ROCM_PLATFORM_VERSION value set (#4353 ) - Set the value of this expected variable to fix build failures.	2025-02-06 17:06:29 -05:00
Peter Park	2751a17cf0	Update vLLM benchmarking guide (#4347 ) * update vllm-benchmark fix hlist overflow update standalone benchmarking options update list of models fix typo and model name unnecessary duplicate info update formatting update vllm benchmark guide - remove Llama 2 FP8 - add Jais 13B - update commands update docker pull tag update MAD available models remove extra mad models not relevant to vllm update PyTorch version add changelog add model names to .wordlist.txt * Update docs/how-to/rocm-for-ai/inference/vllm-benchmark.rst Co-authored-by: Pratik Basyal <pratik.basyal@amd.com> * Update docs/how-to/rocm-for-ai/inference/vllm-benchmark.rst Co-authored-by: Pratik Basyal <pratik.basyal@amd.com> * Update docs/how-to/rocm-for-ai/inference/vllm-benchmark.rst Co-authored-by: Pratik Basyal <pratik.basyal@amd.com> * fix typo * update link * fix link text * change changelog to previous versions * fix typo * remove "for" --------- Co-authored-by: Pratik Basyal <pratik.basyal@amd.com>	2025-02-05 17:18:35 -05:00
Peter Park	9b0ae86b1b	Fix ROCm Bandwidth Test license type Fix ROCm Bandwidth Test license type	2025-02-05 16:40:31 -05:00
harkgill-amd	16f7cb4c04	Update issue workflow to trigger on edit (#4346 )	2025-02-05 14:46:16 -05:00
harkgill-amd	de007b6faf	Update issue_retrieval.yml (#4342 )	2025-02-05 13:21:44 -05:00
Daniel Su	aa1333269c	Ex CI: add ROCM_PATH to rocBLAS (#4343 )	2025-02-05 13:20:36 -05:00
Pratik Basyal	acb8f60304	Radeon support note updated in 6.3.2 (#4339 )	2025-02-04 17:44:24 -05:00
Istvan Kiss	faa67965dd	Precision support page update	2025-02-04 16:17:31 +01:00
Daniel Su	7179f2a72f	Ex CI: add REPO_RADEON_VERSION as a global variable, clean up other variables (#4334 )	2025-02-03 16:04:07 -05:00
Daniel Su	0df0f74312	Ex CI: rocprof-sdk & rocprof-systems VCN tracing dependencies (#4332 )	2025-02-03 11:00:52 -05:00
Pratik Basyal	f885b5df6e	Updated ROCm install on Linux installation method link (#4313 )	2025-01-31 16:48:33 -05:00
dependabot[bot]	ee70cb0bb5	Build(deps): Bump rocm-docs-core from 1.13.0 to 1.15.0 in /docs/sphinx (#4315 ) Bumps [rocm-docs-core](https://github.com/ROCm/rocm-docs-core) from 1.13.0 to 1.15.0. - [Release notes](https://github.com/ROCm/rocm-docs-core/releases) - [Changelog](https://github.com/ROCm/rocm-docs-core/blob/develop/CHANGELOG.md) - [Commits](https://github.com/ROCm/rocm-docs-core/compare/v1.13.0...v1.15.0) --- updated-dependencies: - dependency-name: rocm-docs-core dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>	2025-01-29 17:14:55 -07:00
Jeffrey Novotny	d401b5f152	Add ToC and index links to the AI Developer Tutorials (#4312 ) * Add ToC and index links to the AI Developer Tutorials * Change link positioning * Change wording	2025-01-29 14:43:32 -05:00