Use intersphinx links for deep learning (#5859 )

* Use intersphinx links for deep learning * Update deep-learning-rocm.rst remove Taichi * Update deep-learning-rocm.rst Change Install link to "link" * Apply suggestion from @randyh62 OK
Taichi removed (#5791 )
2026-01-20 20:18:15 -05:00 · 2026-01-20 09:12:31 -08:00 · 2025-12-19 15:43:17 -05:00 · 2025-12-01 19:52:36 +01:00 · 2025-11-26 16:36:03 -05:00 · 2025-11-24 11:57:54 -05:00
29 changed files with 699 additions and 392 deletions
--- a/.azuredevops/components/rocWMMA.yml
+++ b/.azuredevops/components/rocWMMA.yml
@@ -1,29 +1,10 @@
 parameters:
- name: componentName
-  type: string
-  default: rocWMMA
 - 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
@@ -85,11 +66,7 @@ parameters:

 jobs:
 - ${{ each job in parameters.jobMatrix.buildJobs }}:
-  - job: ${{ parameters.componentName }}_build_${{ job.target }}
-    ${{ if parameters.buildDependsOn }}:
-      dependsOn:
-        - ${{ each build in parameters.buildDependsOn }}:
-          - ${{ build }}_${{ job.target }}
+  - job: rocWMMA_build_${{ job.target }}
    variables:
    - group: common
    - template: /.azuredevops/variables-global.yml
@@ -104,7 +81,6 @@ 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 }}
@@ -126,12 +102,9 @@ jobs:
  # gfx1030 not supported in documentation
    - 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
@@ -139,45 +112,43 @@ jobs:
        aptPackages: ${{ parameters.aptPackages }}
        gpuTarget: ${{ job.target }}

- ${{ if eq(parameters.unifiedBuild, False) }}:
-  - ${{ each job in parameters.jobMatrix.testJobs }}:
-    - job: ${{ parameters.componentName }}_test_${{ job.target }}
-      timeoutInMinutes: 270
-      dependsOn: ${{ parameters.componentName }}_build_${{ 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:
-      - 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 }}
-      - 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/rocwmma'
-      - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
-        parameters:
-          aptPackages: ${{ parameters.aptPackages }}
-          environment: test
-          gpuTarget: ${{ job.target }}
+- ${{ each job in parameters.jobMatrix.testJobs }}:
+  - job: rocWMMA_test_${{ job.target }}
+    timeoutInMinutes: 270
+    dependsOn: rocWMMA_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: ${{ variables.CI_TEMPLATE_PATH }}/steps/test.yml
+      parameters:
+        componentName: rocWMMA
+        testDir: '$(Agent.BuildDirectory)/rocm/bin/rocwmma'
+    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/docker-container.yml
+      parameters:
+        aptPackages: ${{ parameters.aptPackages }}
+        environment: test
+        gpuTarget: ${{ job.target }}
--- a/.azuredevops/components/rocm-examples.yml
+++ b/.azuredevops/components/rocm-examples.yml
@@ -21,25 +21,11 @@ parameters:
    - libtbb-dev
    - libtiff-dev
    - libva-amdgpu-dev
-    - libva2-amdgpu
-    - mesa-amdgpu-va-drivers
    - libavcodec-dev
    - libavformat-dev
    - libavutil-dev
    - ninja-build
    - python3-pip
-    - protobuf-compiler
-    - libprotoc-dev
- name: pipModules
-  type: object
-  default:
-    - future==1.0.0
-    - pytz==2022.1
-    - numpy==1.23
-    - google==3.0.0
-    - protobuf==3.12.4
-    - onnx==1.12.0
-    - nnef==1.0.7
 - name: rocmDependencies
  type: object
  default:
@@ -47,7 +33,6 @@ parameters:
    - aomp
    - aomp-extras
    - clr
-    - half
    - composable_kernel
    - hipBLAS
    - hipBLAS-common
@@ -62,7 +47,6 @@ parameters:
    - llvm-project
    - MIOpen
    - MIVisionX
-    - rccl
    - rocALUTION
    - rocBLAS
    - rocDecode
@@ -85,7 +69,6 @@ parameters:
    - aomp
    - aomp-extras
    - clr
-    - half
    - composable_kernel
    - hipBLAS
    - hipBLAS-common
@@ -100,7 +83,6 @@ parameters:
    - llvm-project
    - MIOpen
    - MIVisionX
-    - rccl
    - rocALUTION
    - rocBLAS
    - rocDecode
--- a/.azuredevops/components/rocprofiler-sdk.yml
+++ b/.azuredevops/components/rocprofiler-sdk.yml
@@ -131,11 +131,6 @@ jobs:
        script: |
          USER_BASE=$(python3 -m site --user-base)
          echo "##vso[task.prependpath]$USER_BASE/bin"
-    - task: Bash@3
-      displayName: libelf hack
-      inputs:
-        targetType: inline
-        script: cp $(Agent.BuildDirectory)/s/cmake/Modules/Findlibelf.cmake $(Agent.BuildDirectory)/s/cmake/Modules/FindLibElf.cmake
    - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/build-cmake.yml
      parameters:
        componentName: ${{ parameters.componentName }}
--- a/.azuredevops/templates/steps/dependencies-rocm.yml
+++ b/.azuredevops/templates/steps/dependencies-rocm.yml
@@ -263,7 +263,7 @@ parameters:
      developBranch: develop
      hasGpuTarget: true
    rocWMMA:
-      pipelineId: 370
+      pipelineId: 109
      developBranch: develop
      hasGpuTarget: true
    rpp:
--- a/.gitignore
+++ b/.gitignore
@@ -1,6 +1,7 @@
 .venv
 .vscode
 build
+__pycache__

 # documentation artifacts
 _build/
--- a/.wordlist.txt
+++ b/.wordlist.txt
@@ -36,6 +36,7 @@ Andrej
 Arb
 Autocast
 autograd
+Backported
 BARs
 BatchNorm
 BLAS
@@ -139,6 +140,7 @@ EoS
 etcd
 fas
 FBGEMM
+FiLM
 FIFOs
 FFT
 FFTs
@@ -159,10 +161,12 @@ Fortran
 Fuyu
 GALB
 GAT
+GATNE
 GCC
 GCD
 GCDs
 GCN
+GCNN
 GDB
 GDDR
 GDR
@@ -181,6 +185,8 @@ Glibc
 GLXT
 Gloo
 GMI
+GNN
+GNNs
 GPG
 GPR
 GPT
@@ -196,9 +202,11 @@ GenAI
 GenZ
 GitHub
 Gitpod
+hardcoded
 HBM
 HCA
 HGX
+HLO
 HIPCC
 hipDataType
 HIPExtension
@@ -250,6 +258,7 @@ Intersphinx
 Intra
 Ioffe
 JAX's
+JAXLIB
 Jinja
 JSON
 Jupyter
@@ -321,6 +330,7 @@ MoEs
 Mooncake
 Mpops
 Multicore
+multihost
 Multithreaded
 MXFP
 MyEnvironment
@@ -385,6 +395,7 @@ perf
 PEQT
 PIL
 PILImage
+PJRT
 POR
 PRNG
 PRs
@@ -507,8 +518,6 @@ TPS
 TPU
 TPUs
 TSME
-Taichi
-Taichi's
 Tagram
 TensileLite
 TensorBoard
@@ -1010,6 +1019,7 @@ uncacheable
 uncorrectable
 underoptimized
 unhandled
+unfused
 uninstallation
 unmapped
 unsqueeze
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -49,7 +49,7 @@ for a complete overview of this release.
 * Fixed certain output in `amd-smi monitor` when GPUs are partitioned. It fixes the issue with amd-smi monitor such as: `amd-smi monitor -Vqt`, `amd-smi monitor -g 0 -Vqt -w 1`, and `amd-smi monitor -Vqt --file /tmp/test1`. These commands will now be able to display as normal in partitioned GPU scenarios.

 ```{note}
-See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md) for details, examples, and in-depth descriptions.
+See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md#amd_smi_lib-for-rocm-710) for details, examples, and in-depth descriptions.
 ```

 ### **Composable Kernel** (1.1.0)
@@ -493,7 +493,7 @@ See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/roc
  * Enabled `TCP_TCP_LATENCY` counter and associated counter for all GPUs except MI300.
 * Interactive metric descriptions in TUI analyze mode.
  * You can now left click on any metric cell to view detailed descriptions in the dedicated `METRIC DESCRIPTION` tab.
-* Support for analysis report output as a sqlite database using ``--output-format db`` analysis mode option.
+* Support for analysis report output as a SQLite database using ``--output-format db`` analysis mode option.
 * `Compute Throughput` panel to TUI's `High Level Analysis` category with the following metrics: VALU FLOPs, VALU IOPs, MFMA FLOPs (F8), MFMA FLOPs (BF16), MFMA FLOPs (F16), MFMA FLOPs (F32), MFMA FLOPs (F64), MFMA FLOPs (F6F4) (in gfx950), MFMA IOPs (Int8), SALU Utilization, VALU Utilization, MFMA Utilization, VMEM Utilization, Branch Utilization, IPC

 * `Memory Throughput` panel to TUI's `High Level Analysis` category with the following metrics: vL1D Cache BW, vL1D Cache Utilization, Theoretical LDS Bandwidth, LDS Utilization, L2 Cache BW, L2 Cache Utilization, L2-Fabric Read BW, L2-Fabric Write BW, sL1D Cache BW, L1I BW, Address Processing Unit Busy, Data-Return Busy, L1I-L2 Bandwidth, sL1D-L2 BW
@@ -579,7 +579,7 @@ See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/roc
 * MI300A/X L2-Fabric 64B read counter may display negative values - The rocprof-compute metric 17.6.1 (Read 64B) can report negative values due to incorrect calculation when TCC_BUBBLE_sum + TCC_EA0_RDREQ_32B_sum exceeds TCC_EA0_RDREQ_sum.
  * A workaround has been implemented using max(0, calculated_value) to prevent negative display values while the root cause is under investigation.
 * The profile mode crashes when `--format-rocprof-output json` is selected.
-  * As a workaround, this option should either not be provided or should be set to `csv` instead of `json`. This issue does not affect the profiling results since both `csv` and `json` output formats lead to the same profiling data.  
+    * As a workaround, this option should either not be provided or should be set to `csv` instead of `json`. This issue does not affect the profiling results since both `csv` and `json` output formats lead to the same profiling data.  

 ### **ROCm Data Center Tool** (1.2.0)

@@ -620,6 +620,14 @@ See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/roc
 - Updated PAPI module to v7.2.0b2.
 - ROCprofiler-SDK is now used for tracing OMPT API calls.

+#### Known issues
+
+* Profiling PyTorch and other AI workloads might fail because it is unable to find the libraries in the default linker path. As a workaround, you need to explicitly add the library path to ``LD_LIBRARY_PATH``. For example, when using PyTorch with Python 3.10, add the following to the environment:
+
+```
+export LD_LIBRARY_PATH=:/opt/venv/lib/python3.10/site-packages/torch/lib:$LD_LIBRARY_PATH
+```
+
 ### **rocPRIM** (4.1.0)

 #### Added
@@ -697,17 +705,12 @@ As of ROCm 7.0, the internal error state is cleared on each call to `hipGetLastE

 ### **rocSOLVER** (3.31.0)

-#### Added
-
-* Hybrid computation support for existing routines: STEQR
-
 #### Optimized

 Improved the performance of:

-* BDSQR and downstream functions such as GESVD.
-* STEQR and downstream functions such as SYEV/HEEV.
-* LARFT and downstream functions such as GEQR2 and GEQRF.
+* LARF, LARFT, GEQR2, and downstream functions such as GEQRF.
+* STEDC and divide and conquer Eigensolvers.

 ### **rocSPARSE** (4.1.0)

@@ -1543,8 +1546,8 @@ HIP runtime has the following functional improvements which improves runtime per

 #### Upcoming changes

-* `__AMDGCN_WAVEFRONT_SIZE__` macro and HIP’s `warpSize` variable as `constexpr` are deprecated and will be disabled in a future release. Users are encouraged to update their code if needed to ensure future compatibility. For more information, see [AMDGCN_WAVEFRONT_SIZE deprecation](#amdgpu-wavefront-size-compiler-macro-deprecation).
-* The `roc-obj-ls` and `roc-obj-extract` tools are  deprecated. To extract all Clang offload bundles into separate code objects use `llvm-objdump --offloading <file>`. For more information, see [Changes to ROCm Object Tooling](#changes-to-rocm-object-tooling). 
+* `__AMDGCN_WAVEFRONT_SIZE__` macro and HIP’s `warpSize` variable as `constexpr` are deprecated and will be disabled in a future release. Users are encouraged to update their code if needed to ensure future compatibility. For more information, see [AMDGCN_WAVEFRONT_SIZE deprecation](https://rocm.docs.amd.com/en/docs-7.0.0/about/release-notes.html#amdgpu-wavefront-size-compiler-macro-deprecation).
+* The `roc-obj-ls` and `roc-obj-extract` tools are  deprecated. To extract all Clang offload bundles into separate code objects use `llvm-objdump --offloading <file>`. For more information, see [Changes to ROCm Object Tooling](https://rocm.docs.amd.com/en/docs-7.0.0/about/release-notes.html#changes-to-rocm-object-tooling). 

 ### **MIGraphX** (2.13.0)

--- a/RELEASE.md
+++ b/RELEASE.md
@@ -117,13 +117,12 @@ firmware, AMD GPU drivers, and the ROCm user space software.
              30.10</td>
      </tr>
      <tr>
-          <td>MI325X</td>
+          <td>MI325X<a href="#footnote2"><sup>[2]</sup></a></td>
          <td>
-              01.25.05.01<br>
              01.25.04.02
          </td>
          <td>
-              30.20.0<br>
+              30.20.0<sup>[*]</sup><br>
              30.10.2<br>
              30.10.1<br>
              30.10<br>
@@ -174,6 +173,7 @@ firmware, AMD GPU drivers, and the ROCm user space software.
 </div>

 <p id="footnote1">[1]: PLDM bundle 01.25.05.00 will be available by November 2025.</p>
+<p id="footnote2">[2]: For AMD Instinct MI325X KVM SR-IOV users, do not use AMD GPU Driver (amdgpu) 30.20.0.</p>

 #### AMD SMI improvement: Set power cap

@@ -317,11 +317,6 @@ matrix](../../docs/compatibility/compatibility-matrix.rst) for the complete list

 Torch-MIGraphX integrates the AMD graph inference engine with the PyTorch ecosystem. It provides a `mgx_module` object that may be invoked in the same manner as any other torch module, but utilizes the MIGraphX inference engine internally. Although Torch-MIGraphX has been available in previous releases, installable WHL files are now officially published.

-#### JAX
-
-* JAX customers can now use Llama-2 with JAX efficiently.
-* The latest public JAX repo is {fab}`github` [rocm-jax](https://github.com/ROCm/rocm-jax/tree/master).
-
 #### TensorFlow
 ROCm 7.1.0 enables support for TensorFlow 2.20.0.

@@ -740,6 +735,10 @@ For a historical overview of ROCm component updates, see the {doc}`ROCm consolid

 * Fixed certain output in `amd-smi monitor` when GPUs are partitioned. It fixes the issue with amd-smi monitor such as: `amd-smi monitor -Vqt`, `amd-smi monitor -g 0 -Vqt -w 1`, and `amd-smi monitor -Vqt --file /tmp/test1`. These commands will now be able to display as normal in partitioned GPU scenarios.

+```{note}
+See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md#amd_smi_lib-for-rocm-710) for details, examples, and in-depth descriptions.
+```
+
 ### **Composable Kernel** (1.1.0)

 #### Added
@@ -1181,7 +1180,7 @@ For a historical overview of ROCm component updates, see the {doc}`ROCm consolid
  * Enabled `TCP_TCP_LATENCY` counter and associated counter for all GPUs except MI300.
 * Interactive metric descriptions in TUI analyze mode.
  * You can now left click on any metric cell to view detailed descriptions in the dedicated `METRIC DESCRIPTION` tab.
-* Support for analysis report output as a sqlite database using ``--output-format db`` analysis mode option.
+* Support for analysis report output as a SQLite database using ``--output-format db`` analysis mode option.
 * `Compute Throughput` panel to TUI's `High Level Analysis` category with the following metrics: VALU FLOPs, VALU IOPs, MFMA FLOPs (F8), MFMA FLOPs (BF16), MFMA FLOPs (F16), MFMA FLOPs (F32), MFMA FLOPs (F64), MFMA FLOPs (F6F4) (in gfx950), MFMA IOPs (Int8), SALU Utilization, VALU Utilization, MFMA Utilization, VMEM Utilization, Branch Utilization, IPC

 * `Memory Throughput` panel to TUI's `High Level Analysis` category with the following metrics: vL1D Cache BW, vL1D Cache Utilization, Theoretical LDS Bandwidth, LDS Utilization, L2 Cache BW, L2 Cache Utilization, L2-Fabric Read BW, L2-Fabric Write BW, sL1D Cache BW, L1I BW, Address Processing Unit Busy, Data-Return Busy, L1I-L2 Bandwidth, sL1D-L2 BW
@@ -1308,6 +1307,14 @@ For a historical overview of ROCm component updates, see the {doc}`ROCm consolid
 - Updated PAPI module to v7.2.0b2.
 - ROCprofiler-SDK is now used for tracing OMPT API calls.

+#### Known issues
+
+* Profiling PyTorch and other AI workloads might fail because it is unable to find the libraries in the default linker path. As a workaround, you need to explicitly add the library path to ``LD_LIBRARY_PATH``. For example, when using PyTorch with Python 3.10, add the following to the environment:
+
+```
+export LD_LIBRARY_PATH=:/opt/venv/lib/python3.10/site-packages/torch/lib:$LD_LIBRARY_PATH
+```
+
 ### **rocPRIM** (4.1.0)

 #### Added
@@ -1385,17 +1392,12 @@ As of ROCm 7.0, the internal error state is cleared on each call to `hipGetLastE

 ### **rocSOLVER** (3.31.0)

-#### Added
-
-* Hybrid computation support for existing STEQR routines.
-
 #### Optimized

 Improved the performance of:

-* BDSQR and downstream functions such as GESVD.
-* STEQR and downstream functions such as SYEV/HEEV.
-* LARFT and downstream functions such as GEQR2 and GEQRF.
+* LARF, LARFT, GEQR2, and downstream functions such as GEQRF.
+* STEDC and divide and conquer Eigensolvers.

 ### **rocSPARSE** (4.1.0)

@@ -1479,10 +1481,10 @@ issues related to individual components, review the [Detailed component changes]

 ### MIGraphX Python API will fail when running on Python 3.13

-Applications using the MIGraphX Python API will fail when running on Python 3.13 and return the error message `AttributeError: module 'migraphx' has no attribute 'parse_onnx'`. The issue doesn't occur when you manually build MIGraphX. For detailed instructions, see [Building from source](https://rocm.docs.amd.com/projects/AMDMIGraphX/en/latest/install/building_migraphx.html). As a workaround, change the Python version to the one found in the installed location:
+Applications using the MIGraphX Python API will fail when running on Python 3.13 and return the error message `AttributeError: module 'migraphx' has no attribute 'parse_onnx'`. The issue doesn't occur when you manually build MIGraphX. For detailed instructions, see [Building from source](https://rocm.docs.amd.com/projects/AMDMIGraphX/en/latest/install/install-migraphx.html#build-migraphx-from-source). As a workaround, change the Python version to the one found in the installed location:

 ```
-ls -l /opt/rocm-7.0.0/lib/libmigraphx_py_*.so
+ls -l /opt/rocm-7.1.0/lib/libmigraphx_py_*.so
 ```
 The issue will be resolved in a future ROCm release. See [GitHub issue #5500](https://github.com/ROCm/ROCm/issues/5500).

@@ -1498,6 +1500,22 @@ ROCgdb might fail when running the `step-schedlock-spurious-waves.exp` test case

 Due to a missing `rocm-core` dependency from the ROCm Bandwidth Test, you can't cleanly uninstall ROCm Bandwidth Test using the `amdgpu-install` script. As a workaround, uninstall ROCm Bandwidth Test manually, using the native package managers. For more information, see [Installation via native package manager](https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/install-methods/package-manager-index.html). The issue will be fixed in a future ROCm release. See [GitHub issue #5611](https://github.com/ROCm/ROCm/issues/5611).

+### OpenBLAS runtime dependency for hipblastlt-test and hipblaslt-bench
+
+Running `hipblaslt-test` or `hipblaslt-bench` without installing the OpenBLAS development package results in the following error:
+```
+libopenblas.so.0: cannot open shared object file: No such file or directory
+```
+As a workaround, first install `libopenblas-dev` or `libopenblas-deve`, depending on the package manager used. The issue will be fixed in a future ROCm release. See [GitHub issue #5639](https://github.com/ROCm/ROCm/issues/5639).
+
+### Reduced precision in gemm_ex operations for rocBLAS and hipBLAS
+
+Some `gemm_ex` operations with `half` or `f32_r` data types might yield 16-bit precision results instead of the expected 32-bit precision when matrix dimensions are m=1 or n=1. The issue results from the optimization that enables `_ex` APIs to use lower precision multiples. It limits the high-precision matrix operations performed in PyTorch with rocBLAS and hipBLAS. The issue will be fixed in a future ROCm release. See [GitHub issue #5640](https://github.com/ROCm/ROCm/issues/5640).
+
+### RCCL profiler plugin failure with AllToAll operations
+
+The RCCL profiler plugin `librccl-profiler.so` might fail with a segmentation fault during `AllToAll` collective operations due to improperly assigned point-to-point task function pointers. This leads to invalid memory access and prevents profiling of `AllToAll` performance. Other operations, like `AllReduce`, are unaffected. It's recommended to avoid using the RCCL profiler plugin with `AllToAll` operations until the fix is available. This issue is resolved in the {fab}`github`[RCCL `develop` branch](https://github.com/ROCm/rccl/tree/develop) and will be part of a future ROCm release. See [GitHub issue #5653](https://github.com/ROCm/ROCm/issues/5653).
+
 ## ROCm resolved issues

 The following are previously known issues resolved in this release. For resolved issues related to
--- a/docs/compatibility/compatibility-matrix-historical-6.0.csv
+++ b/docs/compatibility/compatibility-matrix-historical-6.0.csv
@@ -32,14 +32,13 @@ ROCm Version,7.1.0,7.0.2,7.0.1/7.0.0,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6
      FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,
      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.8, 2.7, 2.6","2.8, 2.7, 2.6","2.7, 2.6, 2.5","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>`,"2.20.0, 2.19.1, 2.18.1","2.19.1, 2.18.1, 2.17.1 [#tf-mi350-past-60]_","2.19.1, 2.18.1, 2.17.1 [#tf-mi350-past-60]_","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>`,0.6.0,0.6.0,0.6.0,0.4.35,0.4.35,0.4.35,0.4.35,0.4.31,0.4.31,0.4.31,0.4.31,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
+      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.7.1,0.6.0,0.6.0,0.4.35,0.4.35,0.4.35,0.4.35,0.4.31,0.4.31,0.4.31,0.4.31,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
      :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat-past-60]_,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,0.3.0.post0,N/A,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-past-60]_,N/A,N/A,N/A,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,N/A
-      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat-past-60]_,N/A,N/A,N/A,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,N/A
+      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat-past-60]_,N/A,N/A,2.4.0,2.4.0,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,N/A
      :doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>` [#megablocks_compat-past-60]_,N/A,N/A,N/A,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,N/A
-      :doc:`Taichi <../compatibility/ml-compatibility/taichi-compatibility>` [#taichi_compat-past-60]_,N/A,N/A,N/A,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,N/A
      :doc:`Ray <../compatibility/ml-compatibility/ray-compatibility>` [#ray_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,2.48.0.post0,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,N/A
-      :doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>` [#llama-cpp_compat-past-60]_,N/A,N/A,b6356,b6356,b6356,b6356,b5997,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:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>` [#llama-cpp_compat-past-60]_,N/A,N/A,b6652,b6356,b6356,b6356,b5997,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:`FlashInfer <../compatibility/ml-compatibility/flashinfer-compatibility>` [#flashinfer_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,v0.2.5,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,N/A
      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.22.0,1.22.0,1.22.0,1.20.0,1.20.0,1.20.0,1.20.0,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
      ,,,,,,,,,,,,,,,,,,,,,
@@ -53,7 +52,7 @@ ROCm Version,7.1.0,7.0.2,7.0.1/7.0.0,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6
      CUB,2.8.5,2.6.0,2.6.0,2.5.0,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
      ,,,,,,,,,,,,,,,,,,,,,
     DRIVER & USER SPACE [#kfd_support-past-60]_,.. _kfd-userspace-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,
-      :doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.20.0, 30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x","30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x","30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x, 6.2.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","6.4.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"
+      :doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.20.0 [#mi325x_KVM-past-60]_, 30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x","30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x","30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x, 6.2.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","6.4.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>`,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0
--- a/docs/compatibility/compatibility-matrix.rst
+++ b/docs/compatibility/compatibility-matrix.rst
@@ -56,7 +56,7 @@ compatibility and system requirements.
      FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix:,,
      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.8, 2.7, 2.6","2.8, 2.7, 2.6","2.6, 2.5, 2.4, 2.3"
      :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.20.0, 2.19.1, 2.18.1","2.19.1, 2.18.1, 2.17.1 [#tf-mi350]_","2.18.1, 2.17.1, 2.16.2"
-      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.6.0,0.6.0,0.4.35
+      :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.7.1,0.6.0,0.4.35
      :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat]_,N/A,N/A,2.4.0
      :doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>` [#llama-cpp_compat]_,N/A,N/A,b5997
      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.22.0,1.22.0,1.20.0
@@ -70,7 +70,7 @@ compatibility and system requirements.
      CUB,2.8.5,2.6.0,2.5.0
      ,,,
      DRIVER & USER SPACE [#kfd_support]_,.. _kfd-userspace-support-compatibility-matrix:,,
-      :doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.20.0, 30.10.2, |br| 30.10.1 [#driver_patch]_, 30.10, 6.4.x","30.10.2, 30.10.1 [#driver_patch]_, |br| 30.10, 6.4.x, 6.3.x","6.4.x, 6.3.x, 6.2.x, 6.1.x"
+      :doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.20.0 [#mi325x_KVM]_, 30.10.2, |br| 30.10.1 [#driver_patch]_, 30.10, 6.4.x","30.10.2, 30.10.1 [#driver_patch]_, |br| 30.10, 6.4.x, 6.3.x","6.4.x, 6.3.x, 6.2.x, 6.1.x"
      ,,,
      ML & COMPUTER VISION,.. _mllibs-support-compatibility-matrix:,,
      :doc:`Composable Kernel <composable_kernel:index>`,1.1.0,1.1.0,1.1.0
@@ -170,7 +170,7 @@ compatibility and system requirements.
 .. [#az-mi300x] Starting ROCm 6.4.0, Azure Linux 3.0 is supported only on AMD Instinct MI300X and AMD Radeon PRO V710 GPUs.
 .. [#rl-700] Rocky Linux 9 is supported only on AMD Instinct MI300X and MI300A GPUs.
 .. [#single-node] **Prior to ROCm 7.0.0** - Debian 12 is supported only on AMD Instinct MI300X GPUs for single-node functionality.
-.. [#mi350x-os-710] AMD Instinct MI355X (gfx950) and MI350X (gfx950) GPUs supports all listed :ref:`supported_distributions` except RHEL 8.10, SLES 15 SP7, Debian 12, Rocky 9, Azure Linux 3.0, and Oracle Linux 8.
+.. [#mi350x-os-710] AMD Instinct MI355X (gfx950) and MI350X (gfx950) GPUs supports all listed :ref:`supported_distributions` except RHEL 8.10, SLES 15 SP7, Debian 12, Debian 13, Rocky 9, Azure Linux 3.0, and Oracle Linux 8.
 .. [#mi350x-os-700] AMD Instinct MI355X (gfx950) and MI350X (gfx950) GPUs only supports Ubuntu 24.04.3, Ubuntu 22.04.5, RHEL 10.0, RHEL 9.6, RHEL 9.4, Oracle Linux 10, and Oracle Linux 9.
 .. [#RDNA-OS-700] **For ROCm 7.0.x** - AMD Radeon PRO AI PRO R9700 (gfx1201), AMD Radeon RX 9070 XT (gfx1201), AMD Radeon RX 9070 GRE (gfx1201), AMD Radeon RX 9070 (gfx1201), AMD Radeon RX 9060 XT (gfx1200), AMD Radeon RX 9060 (gfx1200), AMD Radeon RX 7800 XT (gfx1101), AMD Radeon RX 7700 XT (gfx1101), AMD Radeon PRO W7700 (gfx1101), and AMD Radeon PRO W6800 (gfx1030) only supports Ubuntu 24.04.3, Ubuntu 22.04.5, RHEL 10.0, and RHEL 9.6.
 .. [#rd-v710] **For ROCm 7.0.x** - AMD Radeon PRO V710 (gfx1101) GPUs only supports Ubuntu 24.04.3, Ubuntu 22.04.5, RHEL 10.0, RHEL 9.6, and Azure Linux 3.0.
@@ -183,8 +183,9 @@ compatibility and system requirements.
 .. [#mi100-710-os] **For ROCM 7.1.x** - AMD Instinct MI100 GPUs (gfx908) only supports Ubuntu 24.04.3, Ubuntu 22.04.5, RHEL 10.0, RHEL 9.6, RHEL 9.4, RHEL 8.10, and SLES 15 SP7.
 .. [#mi100-os] **For ROCm 7.0.x** - AMD Instinct MI100 GPUs (gfx908) only supports Ubuntu 24.04.3, Ubuntu 22.04.5, RHEL 10.0, RHEL 9.6, RHEL 9.4, and RHEL 8.10.
 .. [#tf-mi350] TensorFlow 2.17.1 is not supported on AMD Instinct MI350 Series GPUs. Use TensorFlow 2.19.1 or 2.18.1 with MI350 Series GPUs instead.
-.. [#dgl_compat] DGL is supported only on ROCm 6.4.0.
+.. [#dgl_compat] DGL is supported only on ROCm 7.0.0, ROCm 6.4.3 and ROCm 6.4.0.
 .. [#llama-cpp_compat] llama.cpp is supported only on ROCm 7.0.0 and ROCm 6.4.x.
+.. [#mi325x_KVM] For AMD Instinct MI325X KVM SR-IOV users, do not use AMD GPU Driver (amdgpu) 30.20.0.
 .. [#driver_patch] AMD GPU Driver (amdgpu) 30.10.1 is a quality release that resolves an issue identified in the 30.10 release. There are no other significant changes or feature additions in ROCm 7.0.1 from ROCm 7.0.0. AMD GPU Driver (amdgpu) 30.10.1 is compatible with ROCm 7.0.1 and ROCm 7.0.0.
 .. [#kfd_support] As of ROCm 6.4.0, forward and backward compatibility between the AMD GPU Driver (amdgpu) and its user space software is provided up to a year apart. For earlier ROCm releases, the compatibility is provided for +/- 2 releases. The supported 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 AMD GPU Driver support matrix <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/user-kernel-space-compat-matrix.html>`_.
 .. [#ROCT-rocr] Starting from ROCm 6.3.0, the ROCT Thunk Interface is included as part of the ROCr runtime package.
@@ -303,12 +304,12 @@ Expand for full historical view of:
   .. [#tf-mi350-past-60] TensorFlow 2.17.1 is not supported on AMD Instinct MI350 Series GPUs. Use TensorFlow 2.19.1 or 2.18.1 with MI350 Series GPUs instead.
   .. [#verl_compat-past-60] verl is supported only on ROCm 6.2.0.
   .. [#stanford-megatron-lm_compat-past-60] Stanford Megatron-LM is supported only on ROCm 6.3.0.
-   .. [#dgl_compat-past-60] DGL is supported only on ROCm 6.4.0.
+   .. [#dgl_compat-past-60] DGL is supported only on ROCm 7.0.0, ROCm 6.4.3 and ROCm 6.4.0.
   .. [#megablocks_compat-past-60] Megablocks is supported only on ROCm 6.3.0.
-   .. [#taichi_compat-past-60] Taichi is supported only on ROCm 6.3.2.
   .. [#ray_compat-past-60] Ray is supported only on ROCm 6.4.1.
   .. [#llama-cpp_compat-past-60] llama.cpp is supported only on ROCm 7.0.0 and 6.4.x.
   .. [#flashinfer_compat-past-60] FlashInfer is supported only on ROCm 6.4.1.
+   .. [#mi325x_KVM-past-60] For AMD Instinct MI325X KVM SR-IOV users, do not use AMD GPU Driver (amdgpu) 30.20.0.
   .. [#driver_patch-past-60] AMD GPU Driver (amdgpu) 30.10.1 is a quality release that resolves an issue identified in the 30.10 release. There are no other significant changes or feature additions in ROCm 7.0.1 from ROCm 7.0.0. AMD GPU Driver (amdgpu) 30.10.1 is compatible with ROCm 7.0.1 and ROCm 7.0.0.
   .. [#kfd_support-past-60] As of ROCm 6.4.0, forward and backward compatibility between the AMD GPU Driver (amdgpu) and its user space software is provided up to a year apart. For earlier ROCm releases, the compatibility is provided for +/- 2 releases. The supported 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 AMD GPU Driver 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.
--- a/docs/compatibility/ml-compatibility/dgl-compatibility.rst
+++ b/docs/compatibility/ml-compatibility/dgl-compatibility.rst
@@ -39,13 +39,13 @@ Support overview
 Version support
 --------------------------------------------------------------------------------

-DGL is supported on `ROCm 6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__.
+DGL is supported on `ROCm 7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__, 
+`ROCm 6.4.3 <https://repo.radeon.com/rocm/apt/6.4.3/>`__, and `ROCm 6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__.

 Supported devices
 --------------------------------------------------------------------------------

- **Officially Supported**: AMD Instinct™ MI300X (through `hipBLASlt <https://rocm.docs.amd.com/projects/hipBLASLt/en/latest/index.html>`__)
- **Partially Supported**: AMD Instinct™ MI250X
+**Officially Supported**: AMD Instinct™ MI300X, MI250X

 .. _dgl-recommendations:

@@ -60,16 +60,35 @@ GAT, GCN, and GraphSage. Using these models, a variety of use cases are supporte
 - 1D (Temporal) and 2D (Image) Classification
 - Drug Discovery

-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. 
+For use cases and recommendations, refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__, 
+where you can search for DGL examples and best practices to optimize your workloads on AMD GPUs.

-Coverage includes:
+* Although multiple use cases of DGL have been tested and verified, a few have been  
+  outlined in the `DGL in the Real World: Running GNNs on Real Use Cases 
+  <https://rocm.blogs.amd.com/artificial-intelligence/dgl_blog2/README.html>`__ blog 
+  post, which walks through four real-world graph neural network (GNN) workloads 
+  implemented with the Deep Graph Library on ROCm. It covers tasks ranging from 
+  heterogeneous e-commerce graphs and multiplex networks (GATNE) to molecular graph 
+  regression (GNN-FiLM) and EEG-based neurological diagnosis (EEG-GCNN). For each use 
+  case, the authors detail: the dataset and task, how DGL is used, and their experience 
+  porting to ROCm. It is shown that DGL codebases often run without modification, with 
+  seamless integration of graph operations, message passing, sampling, and convolution. 

- Single-GPU training/inference
- Multi-GPU training
+* The `Graph Neural Networks (GNNs) at Scale: DGL with ROCm on AMD Hardware 
+  <https://rocm.blogs.amd.com/artificial-intelligence/why-graph-neural/README.html>`__ 
+  blog post introduces the Deep Graph Library (DGL) and its enablement on the AMD ROCm platform, 
+  bringing high-performance graph neural network (GNN) training to AMD GPUs. DGL bridges 
+  the gap between dense tensor frameworks and the irregular nature of graph data through a 
+  graph-first, message-passing abstraction. Its design ensures scalability, flexibility, and 
+  interoperability across frameworks like PyTorch and TensorFlow. AMD’s ROCm integration 
+  enables DGL to run efficiently on HIP-based GPUs, supported by prebuilt Docker containers 
+  and open-source repositories. This marks a major step in AMD's mission to advance open, 
+  scalable AI ecosystems beyond traditional architectures.

+You can pre-process datasets and begin training on AMD GPUs through:
+
+* Single-GPU training/inference
+* Multi-GPU training

 .. _dgl-docker-compat:

@@ -85,7 +104,7 @@ with ROCm backends on Docker Hub. The following Docker image tags and associated
 inventories represent the latest available DGL version from the official Docker Hub. 
 Click the |docker-icon| to view the image on Docker Hub.

-.. list-table:: DGL Docker image components
+.. list-table::
    :header-rows: 1
    :class: docker-image-compatibility

@@ -98,43 +117,83 @@ Click the |docker-icon| to view the image on Docker Hub.

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu24.04_py3.12_pytorch_release_2.6.0/images/sha256-8ce2c3bcfaa137ab94a75f9e2ea711894748980f57417739138402a542dd5564"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4.0.amd0_rocm7.0.0_ubuntu24.04_py3.12_pytorch_2.8.0/images/sha256-943698ddf54c22a7bcad2e5b4ff467752e29e4ba6d0c926789ae7b242cbd92dd"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>

-      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__.
+      - `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
-      - `2.6.0 <https://github.com/ROCm/pytorch/tree/release/2.6>`__
+      - `2.8.0 <https://github.com/pytorch/pytorch/releases/tag/v2.8.0>`__
      - 24.04
      - `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu24.04_py3.12_pytorch_release_2.4.1/images/sha256-cf1683283b8eeda867b690229c8091c5bbf1edb9f52e8fb3da437c49a612ebe4"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4.0.amd0_rocm7.0.0_ubuntu24.04_py3.12_pytorch_2.6.0/images/sha256-b2ec286a035eb7d0a6aab069561914d21a3cac462281e9c024501ba5ccedfbf7"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>

-      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__.
+      - `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
-      - `2.4.1 <https://github.com/ROCm/pytorch/tree/release/2.4>`__
+      - `2.6.0 <https://github.com/pytorch/pytorch/releases/tag/v2.6.0>`__
+      - 24.04
+      - `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4.0.amd0_rocm7.0.0_ubuntu22.04_py3.10_pytorch_2.7.1/images/sha256-d27aee16df922ccf0bcd9107bfcb6d20d34235445d456c637e33ca6f19d11a51"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>
+
+      - `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
+      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
+      - `2.7.1 <https://github.com/pytorch/pytorch/releases/tag/v2.7.1>`__
+      - 22.04
+      - `3.10.16 <https://www.python.org/downloads/release/python-31016/>`__
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4.0.amd0_rocm6.4.3_ubuntu24.04_py3.12_pytorch_2.6.0/images/sha256-f3ba6a3c9ec9f6c1cde28449dc9780e0c4c16c4140f4b23f158565fbfd422d6b"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>
+
+      - `6.4.3 <https://repo.radeon.com/rocm/apt/6.4.3/>`__
+      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
+      - `2.6.0 <https://github.com/pytorch/pytorch/releases/tag/v2.6.0>`__
+      - 24.04
+      - `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu24.04_py3.12_pytorch_release_2.6.0/images/sha256-8ce2c3bcfaa137ab94a75f9e2ea711894748980f57417739138402a542dd5564"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>
+
+      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__
+      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
+      - `2.6.0 <https://github.com/pytorch/pytorch/releases/tag/v2.6.0>`__
+      - 24.04
+      - `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
+
+    * - .. raw:: html
+
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu24.04_py3.12_pytorch_release_2.4.1/images/sha256-cf1683283b8eeda867b690229c8091c5bbf1edb9f52e8fb3da437c49a612ebe4"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>
+
+      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__
+      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
+      - `2.4.1 <https://github.com/pytorch/pytorch/releases/tag/v2.4.1>`__
      - 24.04
      - `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__


    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu22.04_py3.10_pytorch_release_2.4.1/images/sha256-4834f178c3614e2d09e89e32041db8984c456d45dfd20286e377ca8635686554"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu22.04_py3.10_pytorch_release_2.4.1/images/sha256-4834f178c3614e2d09e89e32041db8984c456d45dfd20286e377ca8635686554"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>

-      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__.
+      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__
      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
-      - `2.4.1 <https://github.com/ROCm/pytorch/tree/release/2.4>`__
+      - `2.4.1 <https://github.com/pytorch/pytorch/releases/tag/v2.4.1>`__
      - 22.04
      - `3.10.16 <https://www.python.org/downloads/release/python-31016/>`__


    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu22.04_py3.10_pytorch_release_2.3.0/images/sha256-88740a2c8ab4084b42b10c3c6ba984cab33dd3a044f479c6d7618e2b2cb05e69"><i class="fab fa-docker fa-lg"></i></a>
+           <a href="https://hub.docker.com/layers/rocm/dgl/dgl-2.4_rocm6.4_ubuntu22.04_py3.10_pytorch_release_2.3.0/images/sha256-88740a2c8ab4084b42b10c3c6ba984cab33dd3a044f479c6d7618e2b2cb05e69"><i class="fab fa-docker fa-lg"></i> rocm/dgl</a>

-      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__.
+      - `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__
      - `2.4.0 <https://github.com/dmlc/dgl/releases/tag/v2.4.0>`__
-      - `2.3.0 <https://github.com/ROCm/pytorch/tree/release/2.3>`__
+      - `2.3.0 <https://github.com/pytorch/pytorch/releases/tag/v2.3.0>`__
      - 22.04
      - `3.10.16 <https://www.python.org/downloads/release/python-31016/>`__
      
@@ -150,81 +209,102 @@ If you prefer to build it yourself, ensure the following dependencies are instal
    :header-rows: 1

    * - ROCm library
-      - ROCm 6.4.0 Version
+      - ROCm 7.0.0 Version
+      - ROCm 6.4.x Version
      - Purpose
    * - `Composable Kernel <https://github.com/ROCm/composable_kernel>`_
+      - 1.1.0
      - 1.1.0
      - Enables faster execution of core operations like matrix multiplication
        (GEMM), convolutions and transformations.
    * - `hipBLAS <https://github.com/ROCm/hipBLAS>`_
+      - 3.0.0
      - 2.4.0
      - Provides GPU-accelerated Basic Linear Algebra Subprograms (BLAS) for
        matrix and vector operations.
    * - `hipBLASLt <https://github.com/ROCm/hipBLASLt>`_
+      - 1.0.0
      - 0.12.0
      - hipBLASLt is an extension of the hipBLAS library, providing additional
        features like epilogues fused into the matrix multiplication kernel or
        use of integer tensor cores.
    * - `hipCUB <https://github.com/ROCm/hipCUB>`_
+      - 4.0.0
      - 3.4.0
      - Provides a C++ template library for parallel algorithms for reduction,
        scan, sort and select.
    * - `hipFFT <https://github.com/ROCm/hipFFT>`_
+      - 1.0.20
      - 1.0.18
      - Provides GPU-accelerated Fast Fourier Transform (FFT) operations.
    * - `hipRAND <https://github.com/ROCm/hipRAND>`_
+      - 3.0.0
      - 2.12.0
      - Provides fast random number generation for GPUs.
    * - `hipSOLVER <https://github.com/ROCm/hipSOLVER>`_
+      - 3.0.0
      - 2.4.0
      - Provides GPU-accelerated solvers for linear systems, eigenvalues, and
        singular value decompositions (SVD).
    * - `hipSPARSE <https://github.com/ROCm/hipSPARSE>`_
+      - 4.0.1
      - 3.2.0
      - Accelerates operations on sparse matrices, such as sparse matrix-vector
        or matrix-matrix products.
    * - `hipSPARSELt <https://github.com/ROCm/hipSPARSELt>`_
+      - 0.2.4
      - 0.2.3
      - Accelerates operations on sparse matrices, such as sparse matrix-vector
        or matrix-matrix products.
    * - `hipTensor <https://github.com/ROCm/hipTensor>`_
+      - 2.0.0
      - 1.5.0
      - Optimizes for high-performance tensor operations, such as contractions.
    * - `MIOpen <https://github.com/ROCm/MIOpen>`_
+      - 3.5.0
      - 3.4.0
      - Optimizes deep learning primitives such as convolutions, pooling,
        normalization, and activation functions.
    * - `MIGraphX <https://github.com/ROCm/AMDMIGraphX>`_
+      - 2.13.0
      - 2.12.0
      - Adds graph-level optimizations, ONNX models and mixed precision support
        and enable Ahead-of-Time (AOT) Compilation.
    * - `MIVisionX <https://github.com/ROCm/MIVisionX>`_
+      - 3.3.0
      - 3.2.0
      - Optimizes acceleration for computer vision and AI workloads like
        preprocessing, augmentation, and inferencing.
    * - `rocAL <https://github.com/ROCm/rocAL>`_
-      - :version-ref:`rocAL rocm_version`
+      - 3.3.0
+      - 2.2.0
      - Accelerates the data pipeline by offloading intensive preprocessing and
        augmentation tasks. rocAL is part of MIVisionX.
    * - `RCCL <https://github.com/ROCm/rccl>`_
-      - 2.2.0
+      - 2.26.6
+      - 2.22.3
      - Optimizes for multi-GPU communication for operations like AllReduce and
        Broadcast.
    * - `rocDecode <https://github.com/ROCm/rocDecode>`_
+      - 1.0.0
      - 0.10.0
      - Provides hardware-accelerated data decoding capabilities, particularly
        for image, video, and other dataset formats.
    * - `rocJPEG <https://github.com/ROCm/rocJPEG>`_
+      - 1.1.0
      - 0.8.0
      - Provides hardware-accelerated JPEG image decoding and encoding.
    * - `RPP <https://github.com/ROCm/RPP>`_
+      - 2.0.0
      - 1.9.10
      - Speeds up data augmentation, transformation, and other preprocessing steps.
    * - `rocThrust <https://github.com/ROCm/rocThrust>`_
+      - 4.0.0
      - 3.3.0
      - Provides a C++ template library for parallel algorithms like sorting,
        reduction, and scanning.
    * - `rocWMMA <https://github.com/ROCm/rocWMMA>`_
+      - 2.0.0
      - 1.7.0
      - Accelerates warp-level matrix-multiply and matrix-accumulate to speed up matrix
        multiplication (GEMM) and accumulation operations with mixed precision
@@ -253,26 +333,29 @@ Instead of listing them all, support is grouped into the following categories to
 * DGL NN
 * DGL Optim
 * DGL Sparse
-
+* GraphBolt

 Unsupported features
 ================================================================================

-* GraphBolt
-* Partial TF32 Support (MI250X only)
+* TF32 Support (only supported for PyTorch 2.7 and above)
 * Kineto/ROCTracer integration


 Unsupported functions
 ================================================================================

-* ``more_nnz``
+* ``bfs``
 * ``format``
 * ``multiprocess_sparse_adam_state_dict``
-* ``record_stream_ndarray``
 * ``half_spmm``
 * ``segment_mm`` 
 * ``gather_mm_idx_b``
-* ``pgexplainer``
 * ``sample_labors_prob``
 * ``sample_labors_noprob``
+* ``sparse_admin``
+
+Previous versions
+===============================================================================
+See :doc:`rocm-install-on-linux:install/3rd-party/previous-versions/dgl-history` to find documentation for previous releases
+of the ``ROCm/dgl`` Docker image.
--- a/docs/compatibility/ml-compatibility/jax-compatibility.rst
+++ b/docs/compatibility/ml-compatibility/jax-compatibility.rst
@@ -43,6 +43,26 @@ quarterly alongside new ROCm releases. These images undergo full AMD testing.
 `Community ROCm JAX Docker images <https://hub.docker.com/r/rocm/jax-community/tags>`_
 follow upstream JAX releases and use the latest available ROCm version.

+JAX Plugin-PJRT with JAX/JAXLIB compatibility
+================================================================================
+
+Portable JIT Runtime (PJRT) is an open, stable interface for device runtime and
+compiler. The following table details the ROCm version compatibility matrix
+between JAX Plugin–PJRT and JAX/JAXLIB.
+
+.. list-table::
+    :header-rows: 1
+
+    * - JAX Plugin-PJRT
+      - JAX/JAXLIB
+      - ROCm
+    * - 0.7.1
+      - 0.7.1
+      - 7.1.0
+    * - 0.6.0
+      - 0.6.2, 0.6.0
+      - 7.0.2, 7.0.1, 7.0.0
+
 Use cases and recommendations
 ================================================================================

@@ -249,6 +269,33 @@ For a complete and up-to-date list of JAX public modules (for example, ``jax.num
  JAX API modules are maintained by the JAX project and is subject to change.
  Refer to the official Jax documentation for the most up-to-date information.

+Key features and enhancements for ROCm 7.1
+===============================================================================
+
+- Enabled compilation of multihost HLO runner Python bindings.
+
+  - Backported multihost HLO runner bindings and some related changes to
+    :code:`FunctionalHloRunner`.
+
+  - Added :code:`requirements_lock_3_12` to enable building for Python 3.12.
+
+- Removed hardcoded NHWC convolution layout for ``fp16`` precision to address the performance drops for ``fp16`` precision on gfx12xx GPUs.
+
+
+- ROCprofiler-SDK integration:
+
+  - Integrated ROCprofiler-SDK (v3) to XLA to improve profiling of GPU events,
+    support both time-based and step-based profiling.
+
+  - Added unit tests for :code:`rocm_collector` and :code:`rocm_tracer`.
+
+- Added Triton unsupported conversion from ``f8E4M3FNUZ`` to ``fp16`` with
+  rounding mode.
+
+- Introduced :code:`CudnnFusedConvDecomposer` to revert fused convolutions
+  when :code:`ConvAlgorithmPicker` fails to find a fused algorithm, and removed
+  unfused fallback paths from :code:`RocmFusedConvRunner`.
+
 Key features and enhancements for ROCm 7.0
 ===============================================================================

--- a/docs/compatibility/ml-compatibility/llama-cpp-compatibility.rst
+++ b/docs/compatibility/ml-compatibility/llama-cpp-compatibility.rst
@@ -45,7 +45,7 @@ llama.cpp is supported on `ROCm 7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
 Supported devices
 --------------------------------------------------------------------------------

-**Officially Supported**: AMD Instinct™ MI300X, MI325X, MI210
+**Officially Supported**: AMD Instinct™ MI325X, MI300X, MI210

 Use cases and recommendations
 ================================================================================
@@ -109,27 +109,27 @@ Click |docker-icon| to view the image on Docker Hub.

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6356_rocm7.0.0_ubuntu24.04_full/images/sha256-a2ecd635eaa65bb289a9041330128677f3ae88bee6fee0597424b17e38d4903c"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
+           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6652.amd0_rocm7.0.0_ubuntu24.04_full/images/sha256-a94f0c7a598cc6504ff9e8371c016d7a2f93e69bf54a36c870f9522567201f10g"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
      - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6356_rocm7.0.0_ubuntu24.04_server/images/sha256-cb46b47df415addb5ceb6e6fdf0be70bf9d7f6863bbe6e10c2441ecb84246d52"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
+           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6652.amd0_rocm7.0.0_ubuntu24.04_server/images/sha256-be175932c3c96e882dfbc7e20e0e834f58c89c2925f48b222837ee929dfc47ee"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
      - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6356_rocm7.0.0_ubuntu24.04_light/images/sha256-8f8536eec4b05c0ff1c022f9fc6c527ad1c89e6c1ca0906e4d39e4de73edbde9"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
-      - `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
+           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6652.amd0_rocm7.0.0_ubuntu24.04_light/images/sha256-d8ba0c70603da502c879b1f8010b439c8e7fa9f6cbdac8bbbbbba97cb41ebc9e"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
+      - `b6652 <https://github.com/ROCm/llama.cpp/tree/release/b6652>`__
      - `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
      - 24.04

    * - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6356_rocm7.0.0_ubuntu22.04_full/images/sha256-f36de2a3b03ae53e81c85422cb3780368c9891e1ac7884b04403a921fe2ea45d"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
+           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6652.amd0_rocm7.0.0_ubuntu22.04_full/images/sha256-37582168984f25dce636cc7288298e06d94472ea35f65346b3541e6422b678ee"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
      - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6356_rocm7.0.0_ubuntu22.04_server/images/sha256-df15e8ab11a6837cd3736644fec1e047465d49e37d610ab0b79df000371327df"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
+           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6652.amd0_rocm7.0.0_ubuntu22.04_server/images/sha256-7e70578e6c3530c6591cc2c26da24a9ee68a20d318e12241de93c83224f83720"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
      - .. raw:: html

-           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6356_rocm7.0.0_ubuntu22.04_light/images/sha256-4ea2d5bb7964f0ee3ea9b30ba7f343edd6ddfab1b1037669ca7eafad2e3c2bd7"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
-      - `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
+           <a href="https://hub.docker.com/layers/rocm/llama.cpp/llama.cpp-b6652.amd0_rocm7.0.0_ubuntu22.04_light/images/sha256-9a5231acf88b4a229677bc2c636ea3fe78a7a80f558bd80910b919855de93ad5"><i class="fab fa-docker fa-lg"></i> rocm/llama.cpp</a>
+      - `b6652 <https://github.com/ROCm/llama.cpp/tree/release/b6652>`__
      - `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
      - 22.04

--- a/docs/compatibility/ml-compatibility/taichi-compatibility.rst
+++ b/docs/compatibility/ml-compatibility/taichi-compatibility.rst
@@ -1,99 +0,0 @@
-:orphan:
-
-.. meta::
-    :description: Taichi compatibility
-    :keywords: GPU, Taichi, deep learning, framework 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.
-
-Support overview
-================================================================================
-
- The ROCm-supported version of Taichi is maintained in the official `https://github.com/ROCm/taichi 
-  <https://github.com/ROCm/taichi>`__ repository, which differs from the 
-  `https://github.com/taichi-dev/taichi <https://github.com/taichi-dev/taichi>`__ upstream repository.
-
- To get started and install Taichi on ROCm, use the prebuilt :ref:`Docker image <taichi-docker-compat>`, 
-  which includes ROCm, Taichi, and all required dependencies.
-
-  - See the :doc:`ROCm Taichi installation guide <rocm-install-on-linux:install/3rd-party/taichi-install>` 
-    for installation and setup instructions.
-
-  - You can also consult the upstream `Installation guide <https://github.com/taichi-dev/taichi>`__ 
-    for additional context.
-
-Version support
--------------------------------------------------------------------------------
-
-Taichi is supported on `ROCm 6.3.2 <https://repo.radeon.com/rocm/apt/6.3.2/>`__.
-
-Supported devices
--------------------------------------------------------------------------------
-
- **Officially Supported**: AMD Instinct™ MI250X, MI210X (with the exception of Taichi’s GPU rendering system, CGUI)
- **Upcoming Support**: AMD Instinct™ MI300X
-
-.. _taichi-recommendations:
-
-Use cases and recommendations
-================================================================================
-
-* The `Accelerating Parallel Programming in Python with Taichi Lang on AMD GPUs 
-  <https://rocm.blogs.amd.com/artificial-intelligence/taichi/README.html>`__
-  blog highlights Taichi as an open-source programming language designed for high-performance 
-  numerical computation, particularly in domains like real-time physical simulation, 
-  artificial intelligence, computer vision, robotics, and visual effects. Taichi 
-  is embedded in Python and uses just-in-time (JIT) compilation frameworks like 
-  LLVM to optimize execution on GPUs and CPUs. The blog emphasizes the versatility 
-  of Taichi in enabling complex simulations and numerical algorithms, making 
-  it ideal for developers working on compute-intensive tasks. Developers are 
-  encouraged to follow recommended coding patterns and utilize Taichi decorators 
-  for performance optimization, with examples available in the `https://github.com/ROCm/taichi_examples 
-  <https://github.com/ROCm/taichi_examples>`_ repository. Prebuilt Docker images 
-  integrating ROCm, PyTorch, and Taichi are provided for simplified installation 
-  and deployment, making it easier to leverage Taichi for advanced computational workloads.
-
-.. _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 tag and associated inventories 
-represent the latest Taichi version from the official Docker Hub.
-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/>`_
--- a/docs/compatibility/ml-compatibility/tensorflow-compatibility.rst
+++ b/docs/compatibility/ml-compatibility/tensorflow-compatibility.rst
@@ -136,7 +136,7 @@ The following section maps supported data types and GPU-accelerated TensorFlow
 features to their minimum supported ROCm and TensorFlow versions.

 Data types
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+-----------------

 The data type of a tensor is specified using the ``dtype`` attribute or
 argument, and TensorFlow supports a wide range of data types for different use
@@ -254,7 +254,7 @@ are as follows:
      - 1.7

 Features
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+-----------------

 This table provides an overview of key features in TensorFlow and their
 availability in ROCm.
@@ -346,7 +346,7 @@ availability in ROCm.
      - 1.9.2

 Distributed library features
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+-------------------------------------

 Enables developers to scale computations across multiple devices on a single machine or
 across multiple machines.
--- a/docs/conceptual/gpu-isolation.md
+++ b/docs/conceptual/gpu-isolation.md
@@ -34,7 +34,7 @@ Runtime

 ```{code-block} shell
 :caption: Example to expose the 1. device and a device based on UUID.
-export ROCR_VISIBLE_DEVICES="0,GPU-DEADBEEFDEADBEEF"
+export ROCR_VISIBLE_DEVICES="0,GPU-4b2c1a9f-8d3e-6f7a-b5c9-2e4d8a1f6c3b"
 ```

 ### `GPU_DEVICE_ORDINAL`
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -8,6 +8,7 @@ import os
 import shutil
 import sys
 from pathlib import Path
+from subprocess import run

 gh_release_path = os.path.join("..", "RELEASE.md")
 gh_changelog_path = os.path.join("..", "CHANGELOG.md")
@@ -84,6 +85,9 @@ html_context = {"docs_header_version": "7.1.0"}
 if os.environ.get("READTHEDOCS", "") == "True":
    html_context["READTHEDOCS"] = True

+# Check if the branch is a docs/ branch
+official_branch = run(["git", "rev-parse", "--abbrev-ref", "HEAD"], capture_output=True, text=True).stdout.find("docs/")
+
 # configurations for PDF output by Read the Docs
 project = "ROCm Documentation"
 project_path = os.path.abspath(".").replace("\\", "/")
@@ -107,7 +111,6 @@ article_pages = [
    {"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": "compatibility/ml-compatibility/ray-compatibility", "os": ["linux"]},
    {"file": "compatibility/ml-compatibility/llama-cpp-compatibility", "os": ["linux"]},
    {"file": "compatibility/ml-compatibility/flashinfer-compatibility", "os": ["linux"]},
@@ -202,7 +205,7 @@ external_toc_path = "./sphinx/_toc.yml"
 # Add the _extensions directory to Python's search path
 sys.path.append(str(Path(__file__).parent / 'extension'))

-extensions = ["rocm_docs", "sphinx_reredirects", "sphinx_sitemap", "sphinxcontrib.datatemplates", "version-ref", "csv-to-list-table"]
+extensions = ["rocm_docs", "sphinx_reredirects", "sphinx_sitemap", "sphinxcontrib.datatemplates", "remote-content", "version-ref", "csv-to-list-table"]

 compatibility_matrix_file = str(Path(__file__).parent / 'compatibility/compatibility-matrix-historical-6.0.csv')

@@ -216,6 +219,10 @@ html_context = {"docs_header_version": "7.1.0"}
 if os.environ.get("READTHEDOCS", "") == "True":
    html_context["READTHEDOCS"] = True

+html_context["official_branch"] = official_branch
+html_context["version"] = version
+html_context["release"] = release
+
 html_theme = "rocm_docs_theme"
 html_theme_options = {"flavor": "rocm-docs-home"}

--- a/docs/data/reference/precision-support/precision-support.yaml
+++ b/docs/data/reference/precision-support/precision-support.yaml
@@ -32,7 +32,7 @@ library_groups:

      - name: "MIGraphX"
        tag: "migraphx"
-        doc_link: "amdmigraphx:reference/cpp"
+        doc_link: "amdmigraphx:reference/MIGraphX-cpp"
        data_types:
          - type: "int8"
            support: "⚠️"
@@ -290,7 +290,7 @@ library_groups:

      - name: "Tensile"
        tag: "tensile"
-        doc_link: "tensile:reference/precision-support"
+        doc_link: "tensile:src/reference/precision-support"
        data_types:
          - type: "int8"
            support: "✅"
--- a/docs/extension/remote-content.py
+++ b/docs/extension/remote-content.py
@@ -0,0 +1,141 @@
+from docutils import nodes
+from docutils.parsers.rst import Directive
+from docutils.statemachine import ViewList
+from sphinx.util import logging
+from sphinx.util.nodes import nested_parse_with_titles
+import requests
+import re
+
+logger = logging.getLogger(__name__)
+
+class BranchAwareRemoteContent(Directive):
+    """
+    Directive that downloads and includes content from other repositories,
+    matching the branch/tag of the current documentation build.
+
+    Usage:
+    .. remote-content::
+       :repo: owner/repository
+       :path: path/to/file.rst
+       :default_branch: docs/develop  # Branch to use when not on a release
+       :tag_prefix: Docs/  # Optional
+    """
+
+    required_arguments = 0
+    optional_arguments = 0
+    final_argument_whitespace = True
+    has_content = False
+    option_spec = {
+        'repo': str,
+        'path': str,
+        'default_branch': str,  # Branch to use when not on a release tag
+        'start_line': int,      # Include the file from a specific line
+        'tag_prefix': str,      # Prefix for release tags (e.g., 'Docs/')
+    }
+
+    def get_current_version(self):
+        """Get current version/branch being built"""
+        env = self.state.document.settings.env
+        html_context = env.config.html_context
+
+        # Check if building from a tag
+        if "official_branch" in html_context:
+            if html_context["official_branch"] == 0:
+                if "version" in html_context:
+                    # Remove any 'v' prefix
+                    version = html_context["version"]
+                    if re.match(r'^\d+\.\d+\.\d+$', version):
+                        return version
+
+        # Not a version tag, so we'll use the default branch
+        return None
+
+    def get_target_ref(self):
+        """Get target reference for the remote repository"""
+        current_version = self.get_current_version()
+
+        # If it's a version number, use tag prefix and version
+        if current_version:
+            tag_prefix = self.options.get('tag_prefix', '')
+            return f'{tag_prefix}{current_version}'
+
+        # For any other case, use the specified default branch
+        if 'default_branch' not in self.options:
+            logger.warning('No default_branch specified and not building from a version tag')
+            return None
+
+        return self.options['default_branch']
+
+    def construct_raw_url(self, repo, path, ref):
+        """Construct the raw.githubusercontent.com URL"""
+        return f'https://raw.githubusercontent.com/{repo}/{ref}/{path}'
+
+    def fetch_and_parse_content(self, url, source_path):
+        """Fetch content and parse it as RST"""
+        response = requests.get(url)
+        response.raise_for_status()
+        content = response.text
+
+        start_line = self.options.get('start_line', 0)
+
+        # Create ViewList for parsing
+        line_count = 0
+        content_list = ViewList()
+        for line_no, line in enumerate(content.splitlines()):
+            if line_count >= start_line:
+                content_list.append(line, source_path, line_no)
+            line_count+=1 
+
+        # Create a section node and parse content
+        node = nodes.section()
+        nested_parse_with_titles(self.state, content_list, node)
+
+        return node.children
+
+    def run(self):
+        if 'repo' not in self.options or 'path' not in self.options:
+            logger.warning('Both repo and path options are required')
+            return []
+
+        target_ref = self.get_target_ref()
+        if not target_ref:
+            return []
+
+        raw_url = self.construct_raw_url(
+            self.options['repo'],
+            self.options['path'],
+            target_ref
+        )
+
+        try:
+            logger.info(f'Attempting to fetch content from {raw_url}')
+            return self.fetch_and_parse_content(raw_url, self.options['path'])
+        except requests.exceptions.RequestException as e:
+            logger.warning(f'Failed to fetch content from {raw_url}: {str(e)}')
+
+            # If we failed on a tag, try falling back to default_branch
+            if re.match(r'^\d+\.\d+\.\d+$', target_ref) or target_ref.startswith('Docs/'):
+                if 'default_branch' in self.options:
+                    try:
+                        fallback_ref = self.options['default_branch']
+                        logger.info(f'Attempting fallback to {fallback_ref}...')
+
+                        fallback_url = self.construct_raw_url(
+                            self.options['repo'],
+                            self.options['path'],
+                            fallback_ref
+                        )
+
+                        return self.fetch_and_parse_content(fallback_url, self.options['path'])
+                    except requests.exceptions.RequestException as e2:
+                        logger.warning(f'Fallback also failed: {str(e2)}')
+
+            return []
+
+def setup(app):
+    app.add_directive('remote-content', BranchAwareRemoteContent)
+
+    return {
+        'parallel_read_safe': True,
+        'parallel_write_safe': True,
+    }
--- a/docs/how-to/deep-learning-rocm.rst
+++ b/docs/how-to/deep-learning-rocm.rst
@@ -19,127 +19,95 @@ The table below summarizes information about ROCm-enabled deep learning framewor
    :widths: 5 3 6 3

    * - Framework
-      - Installation
+      - Installation guide
      - Installation options
      - GitHub

-    * - `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>
+    * - :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/pytorch-install>`
      - 
-        - `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>`__
+        - Docker image
+        - Wheels package
+        - ROCm Base Docker image
+        - Upstream Docker file
      - .. 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>
+    * - :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
      - 
-        - `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>`__
+        - Docker image
+        - Wheels package

      - .. 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>
+    * - :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/jax-install>`
      - 
-        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/jax-install.html#using-a-prebuilt-docker-image>`__
+        - 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>
+    * - :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/verl-install>`
      - 
-        - `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>`__
+        - Docker image
      - .. 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>
+    * - :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>`
      - 
-        - `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>`__
+        - Docker image
      - .. 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>
+    * - :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/dgl-install>`
      - 
-        - `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>`__
+        - Docker image
      - .. 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>
+    * - :doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/megablocks-install>`
      - 
-        - `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>`__
+        - Docker image
      - .. 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>
+    * - :doc:`Ray <../compatibility/ml-compatibility/ray-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/ray-install>`
      - 
-        - `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>
-
-    * - `Ray <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/ray-compatibility.html>`__
-      - .. raw:: html
-
-          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/ray-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/ray-install.html#using-a-prebuilt-docker-image-with-ray-pre-installed>`__
-        - `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/ray-install.html#install-ray-on-bare-metal-or-a-custom-container>`__
-        - `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/ray-install.html#build-your-own-docker-image>`__
+        - Docker image
+        - Wheels package
+        - ROCm Base Docker image
      - .. raw:: html

          <a href="https://github.com/ROCm/ray"><i class="fab fa-github fa-lg"></i></a>

-    * - `llama.cpp <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/llama-cpp-compatibility.html>`__
-      - .. raw:: html
-
-          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/llama-cpp-install.html"><i class="fas fa-link fa-lg"></i></a>
+    * - :doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/llama-cpp-install>`
      - 
-        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/llama-cpp-install.html#use-a-prebuilt-docker-image-with-llama-cpp-pre-installed>`__
-        - `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/llama-cpp-install.html#build-your-own-docker-image>`__
+        - Docker image
+        - ROCm Base Docker image
      - .. raw:: html

          <a href="https://github.com/ROCm/llama.cpp"><i class="fab fa-github fa-lg"></i></a>

-    * - `FlashInfer <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/flashinfer-compatibility.html>`__
-      - .. raw:: html
-
-          <a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/flashinfer-install.html"><i class="fas fa-link fa-lg"></i></a>
+    * - :doc:`FlashInfer <../compatibility/ml-compatibility/flashinfer-compatibility>`
+      - :doc:`link <rocm-install-on-linux:install/3rd-party/flashinfer-install>`
      - 
-        - `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/flashinfer-install.html#use-a-prebuilt-docker-image-with-flashinfer-pre-installed>`__
-        - `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/flashinfer-install.html#build-your-own-docker-image>`__
+        - Docker image
+        - ROCm Base Docker image
      - .. raw:: html

          <a href="https://github.com/ROCm/flashinfer"><i class="fab fa-github fa-lg"></i></a>
--- a/docs/how-to/rocm-for-ai/inference-optimization/vllm-optimization.rst
+++ b/docs/how-to/rocm-for-ai/inference-optimization/vllm-optimization.rst
@@ -67,7 +67,7 @@ Quick start examples:
   export VLLM_ROCM_USE_AITER=1
   vllm serve MODEL_NAME

-   # Enable only AITER Triton Prefill-Decode (split) attention
+   # Enable AITER Fused MoE and enable Triton Prefill-Decode (split) attention
   export VLLM_ROCM_USE_AITER=1
   export VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1
   export VLLM_ROCM_USE_AITER_MHA=0
@@ -244,14 +244,17 @@ Most users won't need this, but you can override the defaults:
   * - AITER MHA (standard models)
     - ``VLLM_ROCM_USE_AITER=1`` (auto-selects for non-MLA models)

-   * - AITER Triton Prefill-Decode (split)
+   * - vLLM Triton Unified (default)
+     - ``VLLM_ROCM_USE_AITER=0`` (or unset)
+
+   * - Triton Prefill-Decode (split) without AITER
+     - | ``VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1``
+
+   * - Triton Prefill-Decode (split) along with AITER Fused-MoE
     - | ``VLLM_ROCM_USE_AITER=1``
       | ``VLLM_ROCM_USE_AITER_MHA=0``
       | ``VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1``

-   * - vLLM Triton Unified (default)
-     - ``VLLM_ROCM_USE_AITER=0`` (or unset)
-
   * - AITER Unified Attention
     - | ``VLLM_ROCM_USE_AITER=1``
       | ``VLLM_ROCM_USE_AITER_MHA=0``
@@ -269,11 +272,11 @@ Most users won't need this, but you can override the defaults:
       --block-size 1 \
       --tensor-parallel-size 8

-   # Advanced: Use Prefill-Decode split (for short input cases)
+   # Advanced: Use Prefill-Decode split (for short input cases) with AITER Fused-MoE
   VLLM_ROCM_USE_AITER=1 \
   VLLM_ROCM_USE_AITER_MHA=0 \
   VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1 \
-   vllm serve meta-llama/Llama-3.3-70B-Instruct
+   vllm serve meta-llama/Llama-4-Scout-17B-16E

 **Which backend should I choose?**

@@ -352,14 +355,14 @@ vLLM V1 on ROCm provides these attention implementations:

 3. **AITER Triton Prefill–Decode Attention** (hybrid, Instinct MI300X-optimized)

-   * Enable with ``VLLM_ROCM_USE_AITER=1``, ``VLLM_ROCM_USE_AITER_MHA=0``, and ``VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1``
+   * Enable with ``VLLM_V1_USE_PREFILL_DECODE_ATTENTION=1``
   * Uses separate kernels for prefill and decode phases:

     * **Prefill**: ``context_attention_fwd`` Triton kernel
     * **Primary decode**: ``torch.ops._rocm_C.paged_attention`` (custom ROCm kernel optimized for head sizes 64/128, block sizes 16/32, GQA 1–16, context ≤131k; sliding window not supported)
     * **Fallback decode**: ``kernel_paged_attention_2d`` Triton kernel when shapes don't meet primary decode requirements

-   * Usually better compared to unified Triton kernels (both vLLM and AITER variants)
+   * Usually better compared to unified Triton kernels
   * Performance vs AITER MHA varies: AITER MHA is typically faster overall, but Prefill-Decode split may win in short input scenarios
   * The custom paged attention decode kernel is controlled by ``VLLM_ROCM_CUSTOM_PAGED_ATTN`` (default **True**)

@@ -695,7 +698,9 @@ There are two strategies:
 vLLM engine arguments
 =====================

-Selected arguments that often help on ROCm. See `engine args docs <https://docs.vllm.ai/en/latest/serving/engine_args.html>`_ for the full list.
+Selected arguments that often help on ROCm. See `Engine Arguments
+<https://docs.vllm.ai/en/stable/configuration/engine_args.html>`__ in the vLLM
+documentation for the full list.

 Configure --max-num-seqs
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
--- a/docs/how-to/rocm-for-ai/inference/deploy-your-model.rst
+++ b/docs/how-to/rocm-for-ai/inference/deploy-your-model.rst
@@ -22,7 +22,7 @@ See the `GitHub repository <https://github.com/vllm-project/vllm>`_ and `officia
 <https://docs.vllm.ai/>`_ for more information.

 For guidance on using vLLM with ROCm, refer to `Installation with ROCm
-<https://docs.vllm.ai/en/latest/getting_started/amd-installation.html>`_.
+<https://docs.vllm.ai/en/stable/getting_started/installation/gpu.html#amd-rocm>`__.

 vLLM installation
 -----------------
--- a/docs/how-to/rocm-for-ai/system-setup/multi-node-setup.rst
+++ b/docs/how-to/rocm-for-ai/system-setup/multi-node-setup.rst
@@ -277,7 +277,7 @@ PyTorch training

 .. seealso::

-   See :ref:`Training a model with PyTorch <amd-pytorch-multinode-examples>` for more examples and information.
+   See :ref:`Training a model with PyTorch <amd-pytorch-training-multinode-examples>` for more examples and information.

 Megatron-LM
 -----------
--- a/docs/index.md
+++ b/docs/index.md
@@ -65,6 +65,8 @@ ROCm documentation is organized into the following categories:
 * [ROCm libraries](./reference/api-libraries.md)
 * [ROCm tools, compilers, and runtimes](./reference/rocm-tools.md)
 * [GPU hardware specifications](./reference/gpu-arch-specs.rst)
+* [Hardware atomics operation support](./reference/gpu-atomics-operation.rst)
+* [Environment variables](./reference/env-variables.rst)
 * [Data types and precision support](./reference/precision-support.rst)
 * [Graph safe support](./reference/graph-safe-support.rst)
 <!-- markdownlint-enable MD051 -->
--- a/docs/reference/env-variables.rst
+++ b/docs/reference/env-variables.rst
@@ -0,0 +1,173 @@
+.. meta::
+    :description: Environment variables reference
+    :keywords: AMD, ROCm, environment variables, environment, reference, settings
+
+.. role:: cpp(code)
+   :language: cpp
+
+.. _env-variables-reference:
+
+*************************************************************
+ROCm environment variables
+*************************************************************
+
+ROCm provides a set of environment variables that allow users to configure and optimize their development
+and runtime experience. These variables define key settings such as installation paths, platform selection,
+and runtime behavior for applications running on AMD accelerators and GPUs.
+
+This page outlines commonly used environment variables across different components of the ROCm software stack,
+including HIP and ROCR-Runtime. Understanding these variables can help streamline software development and
+execution in ROCm-based environments.
+
+HIP environment variables
+=========================
+
+The following tables list the HIP environment variables.
+
+GPU isolation variables
+--------------------------------------------------------------------------------
+
+.. remote-content::
+   :repo: ROCm/rocm-systems
+   :path: /projects/hip/docs/reference/env_variables/gpu_isolation_hip_env.rst
+   :default_branch: develop
+   :tag_prefix: docs/
+
+
+Profiling variables
+--------------------------------------------------------------------------------
+
+.. remote-content::
+   :repo: ROCm/rocm-systems
+   :path: /projects/hip/docs/reference/env_variables/profiling_hip_env.rst
+   :default_branch: develop
+   :tag_prefix: docs/
+
+
+Debug variables
+--------------------------------------------------------------------------------
+
+.. remote-content::
+   :repo: ROCm/rocm-systems
+   :path: /projects/hip/docs/reference/env_variables/debug_hip_env.rst
+   :default_branch: develop
+   :tag_prefix: docs/
+
+Memory management related variables
+--------------------------------------------------------------------------------
+
+.. remote-content::
+   :repo: ROCm/rocm-systems
+   :path: /projects/hip/docs/reference/env_variables/memory_management_hip_env.rst
+   :default_branch: develop
+   :tag_prefix: docs/
+
+Other useful variables
+--------------------------------------------------------------------------------
+
+.. remote-content::
+   :repo: ROCm/rocm-systems
+   :path: /projects/hip/docs/reference/env_variables/miscellaneous_hip_env.rst
+   :default_branch: develop
+   :tag_prefix: docs/
+
+ROCR-Runtime environment variables
+==================================
+
+The following table lists the ROCR-Runtime environment variables:
+
+.. remote-content::
+   :repo: ROCm/rocm-systems
+   :path: /projects/rocr-runtime/runtime/docs/data/env_variables.rst
+   :default_branch: develop
+   :tag_prefix: docs/
+
+HIPCC environment variables
+===========================
+
+This topic provides descriptions of the HIPCC environment variables.
+
+.. remote-content::
+   :repo: ROCm/llvm-project
+   :path: amd/hipcc/docs/env.rst
+   :default_branch: amd-staging
+   :start_line: 14
+   :tag_prefix: docs/
+
+Environment variables in ROCm libraries
+=======================================
+
+Many ROCm libraries define environment variables for specific tuning, debugging,
+or behavioral control. The table below provides an overview and links to further
+documentation.
+
+.. list-table::
+    :header-rows: 1
+    :widths: 30, 70
+
+    * - Library
+      - Purpose of Environment Variables
+
+    * - :doc:`hipBLASLt <hipblaslt:reference/env-variables>`
+      - Manage logging, debugging, offline tuning, and stream-K configuration
+        for hipBLASLt.
+
+    * - :doc:`hipSPARSELt <hipsparselt:reference/env-variables>`
+      - Control logging, debugging and performance monitoring of hipSPARSELt.
+
+    * - :doc:`rocBLAS <rocblas:reference/env-variables>`
+      - Performance tuning, kernel selection, logging, and debugging for BLAS
+        operations.
+
+    * - :doc:`rocSolver <rocsolver:reference/env_variables>`
+      - Control logging of rocSolver.
+
+    * - :doc:`rocSPARSE <rocsparse:reference/env_variables>`
+      - Control logging of rocSPARSE.
+
+    * - :doc:`MIGraphX <amdmigraphx:reference/MIGraphX-dev-env-vars>`
+      - Control debugging, testing, and model performance tuning options for
+        MIGraphX.
+
+    * - :doc:`MIOpen <miopen:reference/env_variables>`
+      - Control MIOpen logging and debugging, find mode and algorithm behavior
+        and others.
+
+    * - :doc:`MIVisionX <mivisionx:reference/MIVisionX-env-variables>`
+      - Control core OpenVX, GPU/device and debugging/profiling, stitching and
+        chroma key configurations, file I/O operations, model deployment, and
+        neural network parameters of MIVisionX.
+
+    * - :doc:`RCCL <rccl:api-reference/env-variables>`
+      - Control the logging, debugging, compiler and assembly behavior, and
+        cache of RPP.
+
+    * - :doc:`RPP <rpp:reference/rpp-env-variables>`
+      - Logging, debugging, compiler and assembly management, and cache control in RPP
+
+    * - `Tensile <https://rocm.docs.amd.com/projects/Tensile/en/latest/src/reference/environment-variables.html>`_
+      - Enable testing, debugging, and experimental features for Tensile clients and applications
+
+Key single-variable details
+===========================
+
+This section provides detailed descriptions, in the standard format, for ROCm
+libraries that feature a single, key environment variable (or a very minimal set)
+which is documented directly on this page for convenience.
+
+.. _rocalution-vars-detail:
+
+rocALUTION
+----------
+
+.. list-table::
+    :header-rows: 1
+    :widths: 70,30
+
+    * - Environment variable
+      - Value
+
+    * - | ``ROCALUTION_LAYER``
+        | If set to ``1``, enable file logging. Logs each rocALUTION function call including object constructor/destructor, address of the object, memory allocation, data transfers, all function calls for matrices, vectors, solvers, and preconditioners. The log file is placed in the working directory.
+      - | ``1`` (Enable trace file logging)
+        | Default: Not set.
--- a/docs/reference/graph-safe-support.rst
+++ b/docs/reference/graph-safe-support.rst
@@ -93,7 +93,7 @@ The following table shows whether a ROCm library is graph-safe.
      - ⚠️ (experimental)
    * 
      - `rocThrust <https://github.com/ROCm/rocThrust>`_
-      - ❌ (see :doc:`details <rocthrust:hipgraph-support>`)
+      - ❌ (see :doc:`details <rocthrust:reference/rocThrust-hipgraph-support>`)
    * 
      - `rocWMMA <https://github.com/ROCm/rocWMMA>`_
      - ❌
--- a/docs/sphinx/_toc.yml.in
+++ b/docs/sphinx/_toc.yml.in
@@ -25,7 +25,7 @@ subtrees:
    title: HIP SDK on Windows
  - url: https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/index.html
    title: ROCm on Radeon and Ryzen
-  - file: how-to/deep-learning-rocm.md
+  - file: how-to/deep-learning-rocm
    title: Deep learning frameworks
    subtrees:
    - entries:
@@ -43,8 +43,6 @@ subtrees:
        title: DGL compatibility
      - file: compatibility/ml-compatibility/megablocks-compatibility.rst
        title: Megablocks compatibility
-      - file: compatibility/ml-compatibility/taichi-compatibility.rst
-        title: Taichi compatibility
      - file: compatibility/ml-compatibility/ray-compatibility.rst
        title: Ray compatibility
      - file: compatibility/ml-compatibility/llama-cpp-compatibility.rst
@@ -216,6 +214,8 @@ subtrees:
    title: ROCm tools, compilers, and runtimes
  - file: reference/gpu-arch-specs.rst
  - file: reference/gpu-atomics-operation.rst
+  - file: reference/env-variables.rst
+    title: Environment variables
  - file: reference/precision-support.rst
    title: Data types and precision support
  - file: reference/graph-safe-support.rst
--- a/docs/sphinx/requirements.in
+++ b/docs/sphinx/requirements.in
@@ -1,4 +1,4 @@
-rocm-docs-core==1.27.0
+rocm-docs-core==1.30.0
 sphinx-reredirects
 sphinx-sitemap
 sphinxcontrib.datatemplates==0.11.0
--- a/docs/sphinx/requirements.txt
+++ b/docs/sphinx/requirements.txt
@@ -2,13 +2,13 @@
 # This file is autogenerated by pip-compile with Python 3.10
 # by the following command:
 #
-#    pip-compile docs/sphinx/requirements.in
+#    pip-compile requirements.in
 #
 accessible-pygments==0.0.5
    # via pydata-sphinx-theme
 alabaster==1.0.0
    # via sphinx
-asttokens==3.0.0
+asttokens==3.0.1
    # via stack-data
 attrs==25.4.0
    # via
@@ -23,21 +23,21 @@ beautifulsoup4==4.14.2
    # via pydata-sphinx-theme
 breathe==4.36.0
    # via rocm-docs-core
-certifi==2025.10.5
+certifi==2025.11.12
    # via requests
 cffi==2.0.0
    # via
    #   cryptography
    #   pynacl
-charset-normalizer==3.4.3
+charset-normalizer==3.4.4
    # via requests
-click==8.3.0
+click==8.3.1
    # via
    #   jupyter-cache
    #   sphinx-external-toc
 comm==0.2.3
    # via ipykernel
-cryptography==46.0.2
+cryptography==46.0.3
    # via pyjwt
 debugpy==1.8.17
    # via ipykernel
@@ -50,7 +50,7 @@ docutils==0.21.2
    #   myst-parser
    #   pydata-sphinx-theme
    #   sphinx
-exceptiongroup==1.3.0
+exceptiongroup==1.3.1
    # via ipython
 executing==2.2.1
    # via stack-data
@@ -64,7 +64,7 @@ gitpython==3.1.45
    # via rocm-docs-core
 greenlet==3.2.4
    # via sqlalchemy
-idna==3.10
+idna==3.11
    # via requests
 imagesize==1.4.1
    # via sphinx
@@ -72,7 +72,7 @@ importlib-metadata==8.7.0
    # via
    #   jupyter-cache
    #   myst-nb
-ipykernel==6.30.1
+ipykernel==7.1.0
    # via myst-nb
 ipython==8.37.0
    # via
@@ -94,7 +94,7 @@ jupyter-client==8.6.3
    # via
    #   ipykernel
    #   nbclient
-jupyter-core==5.8.1
+jupyter-core==5.9.1
    # via
    #   ipykernel
    #   jupyter-client
@@ -106,7 +106,7 @@ markdown-it-py==3.0.0
    #   myst-parser
 markupsafe==3.0.3
    # via jinja2
-matplotlib-inline==0.1.7
+matplotlib-inline==0.2.1
    # via
    #   ipykernel
    #   ipython
@@ -137,11 +137,11 @@ parso==0.8.5
    # via jedi
 pexpect==4.9.0
    # via ipython
-platformdirs==4.4.0
+platformdirs==4.5.0
    # via jupyter-core
 prompt-toolkit==3.0.52
    # via ipython
-psutil==7.1.0
+psutil==7.1.3
    # via ipykernel
 ptyprocess==0.7.0
    # via pexpect
@@ -163,7 +163,7 @@ pygments==2.19.2
    #   sphinx
 pyjwt[crypto]==2.10.1
    # via pygithub
-pynacl==1.6.0
+pynacl==1.6.1
    # via pygithub
 python-dateutil==2.9.0.post0
    # via jupyter-client
@@ -179,7 +179,7 @@ pyzmq==27.1.0
    # via
    #   ipykernel
    #   jupyter-client
-referencing==0.36.2
+referencing==0.37.0
    # via
    #   jsonschema
    #   jsonschema-specifications
@@ -187,9 +187,9 @@ requests==2.32.5
    # via
    #   pygithub
    #   sphinx
-rocm-docs-core==1.27.0
+rocm-docs-core==1.30.0
    # via -r requirements.in
-rpds-py==0.27.1
+rpds-py==0.29.0
    # via
    #   jsonschema
    #   referencing
@@ -249,13 +249,13 @@ sphinxcontrib-runcmd==0.2.0
    # via sphinxcontrib-datatemplates
 sphinxcontrib-serializinghtml==2.0.0
    # via sphinx
-sqlalchemy==2.0.43
+sqlalchemy==2.0.44
    # via jupyter-cache
 stack-data==0.6.3
    # via ipython
 tabulate==0.9.0
    # via jupyter-cache
-tomli==2.2.1
+tomli==2.3.0
    # via sphinx
 tornado==6.5.2
    # via
Author	SHA1	Message	Date
randyh62	437a6c2849	Use intersphinx links for deep learning (#5859 ) * Use intersphinx links for deep learning * Update deep-learning-rocm.rst remove Taichi * Update deep-learning-rocm.rst Change Install link to "link" * Apply suggestion from @randyh62 OK	2026-01-20 09:12:31 -08:00
Pratik Basyal	4e98d954af	Taichi removed (#5791 )	2025-12-19 15:43:17 -05:00
Istvan Kiss	ad888e854d	JAX key features and enhancements (#5711 ) Co-authored-by: Pratik Basyal <prbasyal@amd.com>	2025-12-01 19:52:36 +01:00
ROCm Docs Automation	00df690446	Update rocm-docs-core to 1.30.0	2025-11-26 16:36:03 -05:00
Pratik Basyal	b094c2ba1a	New link updated for MIgraphx (#5691 ) (#5692 )	2025-11-24 11:57:54 -05:00
Istvan Kiss	64559321cb	Docs: Add Environment Variable Page (#395 ) (#5688 ) Co-authored-by: Adel Johar <adel.johar@amd.com>	2025-11-21 18:56:12 +01:00
Istvan Kiss	cd8d27ba40	Add JAX Plugin-PJRT support table 7.1.0 (#5682 ) * Add JAX Plugin-PJRT support table 7.1.0 Fix JAX version * Update wordlist.txt for JAX comp table	2025-11-20 18:16:19 +01:00
Pratik Basyal	e5c9382825	Changelog updated (#5660 ) (#5661 )	2025-11-13 10:22:45 -05:00
Pratik Basyal	7a7c5b25a6	710 RCCL Known Issues and CRIU note update (#5647 ) (#5654 ) * RCCL ALltoALL known issue added * CRIU note added * Minor change * Review feedback and AMDSMI detailed changelog link added * Github issue link added	2025-11-11 16:59:59 -05:00
peterjunpark	a1a33185b9	Fixed wording related to VLLM_V1_USE_PREFILL_DECODE_ATTENTION (#5605 ) Co-authored-by: Hongxia Yang <hongxia.yang@amd.com> (cherry picked from commit `eb956cfc5c`)	2025-11-11 09:23:39 -05:00
peterjunpark	876da0b68b	Fix references to vLLM docs (#5651 ) (cherry picked from commit `e05cdca54f`)	2025-11-11 09:23:39 -05:00
anisha-amd	508cb9829e	Docs: frameworks 25.10 - compatibility - DGL and llama.cpp (#5648 ) (#5649 )	2025-11-10 15:39:56 -05:00
Alex Xu	5e7a88f769	update rocm-docs-core to 1.29.0 (cherry picked from commit `39de859bd1`)	2025-11-10 14:10:45 -05:00
Pratik Basyal	503d4491de	7.1.0 MI325X PLDM note updated (#5644 ) (#5645 ) * PLDM note updated * Footnote update * Note added to compatibility * Lint error fixed	2025-11-08 09:47:56 -05:00
Pratik Basyal	a43cde5bd8	rocBLAS precision known issue added [Develop] (#5641 ) (#5642 ) * rocBLAS precision known issue added * IPC note removed * Review feedback added	2025-11-07 19:49:34 -05:00
Pratik Basyal	5a1494b7f5	rocBLAS and HipBLASLt known issue added 7.1.0 (#5634 ) (#5637 ) * rocBLAS and HipBLASLt known issue added * Title warning fixed * Jeff's feedback added * Leo's feedback incorporated * Minor feedback * MI325X PLDM udpate * Leo's feedback added * PyTorch profiling issue added * Changelog synced * JAX section removed * Ram's feedback added	2025-11-07 18:05:41 -05:00
yugang-amd	b548b0edec	[7.1 cherry-pick] vLLM 10/24 release (#5628 ) * vLLM 10/24 release * updates per SME inputs * Update docs/how-to/rocm-for-ai/inference/benchmark-docker/vllm.rst Co-authored-by: Jeffrey Novotny <jnovotny@amd.com> --------- Co-authored-by: Jeffrey Novotny <jnovotny@amd.com>	2025-11-05 11:58:43 -05:00
Pratik Basyal	472afbfa6f	ROCm Bandwidth test issue added to 710 release notes [docs/7.1.0] (#5614 ) * 710 known issues update[Batch1] (#5604) (#5608) * Version update * ROCm Bandwidth failure added * Editorial feedback added * Minor change * rocprofv3 issue added * Minor change * ROCgdb issue added * SME feedback incorpprated * Leo's feedback added * ROCm Compute Profiler known issue added * Changelog synced * ROCm Bandwidth test issue added (#5612)	2025-10-31 18:41:53 -04:00
Pratik Basyal	afd388aafb	710 known issues update[Batch1] (#5604 ) (#5608 ) * Version update * ROCm Bandwidth failure added * Editorial feedback added * Minor change * rocprofv3 issue added * Minor change * ROCgdb issue added * SME feedback incorpprated * Leo's feedback added * ROCm Compute Profiler known issue added * Changelog synced	2025-10-31 15:17:35 -04:00
Pratik Basyal	59135e73cd	7.1.0 Post GA updates (#5600 ) (#5601 ) * Post GA updates * Mono repo link added * AMD SMI changelog link removed	2025-10-30 13:31:49 -04:00
amitkumar-amd	c4483379c6	Update compatibility-matrix.rst	2025-10-30 11:24:36 -05:00
amitkumar-amd	fc3091be75	Update RELEASE.md	2025-10-30 11:08:50 -05:00
Alex Xu	dfa04e5c21	Merge branch 'roc-7.1.x' into docs/7.1.0	2025-10-30 11:41:34 -04:00
alexxu-amd	2024aa839e	Sync develop into docs/7.1.0	2025-10-30 09:49:37 -04:00
alexxu-amd	45ab654f39	Sync develop into docs/7.1.0	2025-10-30 09:06:32 -04:00