Precision support page update

Ex CI: add REPO_RADEON_VERSION as a global variable, clean up other variables (#4334 )
Ex CI: rocprof-sdk & rocprof-systems VCN tracing dependencies (#4332 )
2026-01-09 22:58:17 -05:00 · 2025-02-04 15:03:31 +01:00 · 2025-02-03 16:04:07 -05:00 · 2025-02-03 11:00:52 -05:00 · 2025-01-31 16:48:33 -05:00 · 2025-01-29 17:14:55 -07:00
23 changed files with 267 additions and 124 deletions
--- a/.azuredevops/components/rocDecode.yml
+++ b/.azuredevops/components/rocDecode.yml
@@ -49,21 +49,10 @@ jobs:
  workspace:
    clean: all
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -104,21 +93,10 @@ jobs:
        JOB_GPU_TARGET: gfx942
        JOB_TEST_POOL: ${{ variables.GFX942_TEST_POOL }}
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
--- a/.azuredevops/components/rocJPEG.yml
+++ b/.azuredevops/components/rocJPEG.yml
@@ -48,21 +48,10 @@ jobs:
      gfx942:
        JOB_GPU_TARGET: gfx942
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -106,21 +95,10 @@ jobs:
        JOB_GPU_TARGET: gfx942
        JOB_TEST_POOL: ${{ variables.GFX942_TEST_POOL }}
  steps:
-  # Since mesa-amdgpu-multimedia-devel is not directly available from apt, register it
-  - task: Bash@3
-    displayName: 'Register ROCm packages'
-    inputs:
-      targetType: inline
-      script: |
-        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
-        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/${{ variables.KEYRING_VERSION }}/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/${{ variables.KEYRING_VERSION }} jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
-        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
-        sudo apt update
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/local-artifact-download.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-aqlprofile.yml
--- a/.azuredevops/components/rocm-core.yml
+++ b/.azuredevops/components/rocm-core.yml
@@ -36,7 +36,7 @@ jobs:
        -DCPACK_GENERATOR=DEB
        -DCPACK_DEBIAN_PACKAGE_RELEASE="local.9999~99.99"
        -DCPACK_RPM_PACKAGE_RELEASE="local.9999"
-        -DROCM_VERSION="$(next-release)"
+        -DROCM_VERSION="$(NEXT_RELEASE_VERSION)"
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/manifest.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-upload.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/artifact-links.yml
--- a/.azuredevops/components/rocminfo.yml
+++ b/.azuredevops/components/rocminfo.yml
@@ -35,7 +35,7 @@ jobs:
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-other.yml
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
--- a/.azuredevops/components/rocprofiler-sdk.yml
+++ b/.azuredevops/components/rocprofiler-sdk.yml
@@ -37,6 +37,8 @@ parameters:
    - clr
    - llvm-project
    - rccl
+    - rocDecode
+    - rocJPEG
    - rocm-cmake
    - rocm-core
    - rocminfo
@@ -60,7 +62,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -99,6 +101,7 @@ jobs:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
      gpuTarget: $(JOB_GPU_TARGET)
+      registerROCmPackages: true

 - job: rocprofiler_sdk_testing
  dependsOn: rocprofiler_sdk
@@ -119,7 +122,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -155,3 +158,4 @@ jobs:
      pipModules: ${{ parameters.pipModules }}
      environment: test
      gpuTarget: $(JOB_GPU_TARGET)
+      registerROCmPackages: true
--- a/.azuredevops/components/rocprofiler-systems.yml
+++ b/.azuredevops/components/rocprofiler-systems.yml
@@ -46,13 +46,14 @@ parameters:
 - name: rocmDependencies
  type: object
  default:
+    - amdsmi
    - aomp
    - clr
    - llvm-project
    - rccl
    - rocDecode
+    - rocJPEG
    - rocm-core
-    - rocm_smi_lib
    - rocminfo
    - ROCR-Runtime
    - rocprofiler-register
@@ -75,7 +76,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
@@ -159,7 +160,7 @@ jobs:
    parameters:
      aptPackages: ${{ parameters.aptPackages }}
      pipModules: ${{ parameters.pipModules }}
-      registerRadeon: true
+      registerROCmPackages: true
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
  - template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
    parameters:
--- a/.azuredevops/dependencies/half560.yml
+++ b/.azuredevops/dependencies/half560.yml
@@ -19,7 +19,7 @@ jobs:
  pool:
    vmImage: ${{ variables.BASE_BUILD_POOL }}
  container:
-    image: ${{ variables.DOCKER_IMAGE_NAME }}:${{ variables.LATEST_DOCKER_VERSION }}
+    image: rocm/dev-ubuntu-22.04:${{ variables.LATEST_RELEASE_VERSION }}
  workspace:
    clean: all
  steps:
--- a/.azuredevops/templates/steps/dependencies-aqlprofile.yml
+++ b/.azuredevops/templates/steps/dependencies-aqlprofile.yml
@@ -4,13 +4,13 @@ steps:
  inputs:
    targetType: inline
    script: |
-      export packageName=$(curl -s https://repo.radeon.com/rocm/apt/latest/pool/main/h/hsa-amd-aqlprofile/ | grep -oP "href=\"\K[^\"]*$(lsb_release -rs)[^\"]*\.deb")
+      export packageName=$(curl -s https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION)/pool/main/h/hsa-amd-aqlprofile/ | grep -oP "href=\"\K[^\"]*$(lsb_release -rs)[^\"]*\.deb")
      echo "##vso[task.setvariable variable=packageName;isreadonly=true]$packageName"
 - task: Bash@3
  displayName: 'Download aqlprofile'
  inputs:
    targetType: inline
-    script: wget -nv https://repo.radeon.com/rocm/apt/latest/pool/main/h/hsa-amd-aqlprofile/$(packageName)
+    script: wget -nv https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION)/pool/main/h/hsa-amd-aqlprofile/$(packageName)
    workingDirectory: '$(Pipeline.Workspace)'
 - task: Bash@3
  displayName: 'Extract aqlprofile'
--- a/.azuredevops/templates/steps/dependencies-other.yml
+++ b/.azuredevops/templates/steps/dependencies-other.yml
@@ -6,21 +6,21 @@ parameters:
 - name: pipModules
  type: object
  default: []
- name: registerRadeon
+- name: registerROCmPackages
  type: boolean
  default: false

 steps:
- ${{ if eq(parameters.registerRadeon, true) }}:
+- ${{ if eq(parameters.registerROCmPackages, true) }}:
  - task: Bash@3
-    displayName: 'Register repo.radeon packages'
+    displayName: 'Register AMDGPU & ROCm repos'
    inputs:
      targetType: inline
      script: |
        sudo mkdir --parents --mode=0755 /etc/apt/keyrings
        wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | sudo tee /etc/apt/keyrings/rocm.gpg > /dev/null
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/latest/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
-        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/latest jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
+        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/$(REPO_RADEON_VERSION)/ubuntu jammy main" | sudo tee /etc/apt/sources.list.d/amdgpu.list
+        echo "deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION) jammy main" | sudo tee --append /etc/apt/sources.list.d/rocm.list
        echo -e 'Package: *\nPin: release o=repo.radeon.com\nPin-Priority: 600' | sudo tee /etc/apt/preferences.d/rocm-pin-600
        sudo apt update
 # firefox takes time to upgrade and is not needed for CI workloads, hold version
--- a/.azuredevops/templates/steps/docker-container.yml
+++ b/.azuredevops/templates/steps/docker-container.yml
@@ -154,8 +154,8 @@ steps:
        script: |
          echo "RUN mkdir --parents --mode=0755 /etc/apt/keyrings" >> Dockerfile
          echo "RUN wget https://repo.radeon.com/rocm/rocm.gpg.key -O - | gpg --dearmor | tee /etc/apt/keyrings/rocm.gpg > /dev/null" >> Dockerfile
-          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/latest/ubuntu jammy main\" | tee /etc/apt/sources.list.d/amdgpu.list" >> Dockerfile
-          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/latest jammy main\" | tee --append /etc/apt/sources.list.d/rocm.list" >> Dockerfile
+          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/amdgpu/$(REPO_RADEON_VERSION)/ubuntu jammy main\" | tee /etc/apt/sources.list.d/amdgpu.list" >> Dockerfile
+          echo "RUN echo \"deb [arch=amd64 signed-by=/etc/apt/keyrings/rocm.gpg] https://repo.radeon.com/rocm/apt/$(REPO_RADEON_VERSION) jammy main\" | tee --append /etc/apt/sources.list.d/rocm.list" >> Dockerfile
          echo "RUN printf 'Package: *\\nPin: release o=repo.radeon.com\\nPin-Priority: 600' > /etc/apt/preferences.d/rocm-pin-600" >> Dockerfile
          echo "RUN DEBIAN_FRONTEND=noninteractive apt-get --yes update" >> Dockerfile
  - ${{ if eq(parameters.registerCUDAPackages, true) }}:
--- a/.azuredevops/variables-global.yml
+++ b/.azuredevops/variables-global.yml
@@ -27,14 +27,14 @@ variables:
  value: rocm-ci_larger_base_disk_pool
 - name: GFX942_TEST_POOL
  value: gfx942_test_pool
+- name: LATEST_RELEASE_VERSION
+  value: 6.3.2
+- name: REPO_RADEON_VERSION
+  value: 6.3.2
+- name: NEXT_RELEASE_VERSION
+  value: 6.4.0
 - name: LATEST_RELEASE_TAG
-  value: rocm-6.1.0
- name: DOCKER_IMAGE_NAME
-  value: rocm/dev-ubuntu-22.04
- name: LATEST_DOCKER_VERSION
-  value: 6.1
- name: KEYRING_VERSION
-  value: 6.3
+  value: rocm-6.3.2
 - name: AMDMIGRAPHX_GFX942_TEST_PIPELINE_ID
  value: 197
 - name: AMDMIGRAPHX_PIPELINE_ID
@@ -151,8 +151,6 @@ variables:
  value: 105
 - name: HIPTENSOR_TAGGED_PIPELINE_ID
  value: 56
- name: LAST_RELEASE
-  value: 6.1.0
 - name: LLVM_PROJECT_PIPELINE_ID
  value: 2
 - name: LLVM_PROJECT_TAGGED_PIPELINE_ID
@@ -183,10 +181,6 @@ variables:
  value: 100
 - name: RDC_TAGGED_PIPELINE_ID
  value: 59
- name: REIMAGE_ORG
-  value: AGS-ROCm-CI
- name: REIMAGE_REPO
-  value: cirrascale-reimage-automation
 - name: ROCAL_PIPELINE_ID
  value: 151
 - name: ROCALUTION_GFX942_TEST_PIPELINE_ID
--- a/docs/how-to/rocm-for-ai/fine-tuning/index.rst
+++ b/docs/how-to/rocm-for-ai/fine-tuning/index.rst
@@ -16,6 +16,9 @@ Throughout the following topics, this guide discusses the goals and :ref:`challe
 model <fine-tuning-llms-concept-challenge>` like Llama 2. In the
 sections that follow, you'll find practical guides on libraries and tools to accelerate your fine-tuning.

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

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

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

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

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

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

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

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

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

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

 * :doc:`Using the AMDGPU installer <rocm-install-on-linux:install/amdgpu-install>`

--- a/docs/how-to/rocm-for-ai/training/index.rst
+++ b/docs/how-to/rocm-for-ai/training/index.rst
@@ -14,6 +14,9 @@ Training models on AMD GPUs with the ROCm™ software platform allows you to use
 
 The ROCm software platform makes it easier to train models on AMD GPUs while maintaining compatibility with existing code and tools. The platform also provides features like multi-GPU support, allowing for scaling and parallelization of model training across multiple GPUs to enhance performance. 

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

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

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

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

 * [Use ROCm for AI](./how-to/rocm-for-ai/index.rst)
+* [AI tutorials](https://rocm.docs.amd.com/projects/ai-developer-hub/en/latest/)
 * [Use ROCm for HPC](./how-to/rocm-for-hpc/index.rst)
 * [System optimization](./how-to/system-optimization/index.rst)
 * [AMD Instinct MI300X performance validation and tuning](./how-to/tuning-guides/mi300x/index.rst)
--- a/docs/reference/precision-support.rst
+++ b/docs/reference/precision-support.rst
@@ -1,19 +1,23 @@
 .. meta::
-  :description: Supported data types in ROCm
-  :keywords: int8, float8, float8 (E4M3), float8 (E5M2), bfloat8, float16, half, bfloat16, tensorfloat32, float,
-   float32, float64, double, AMD, ROCm, AMDGPU
+  :description: Supported data types of AMD GPUs and libraries in ROCm.
+  :keywords: precision, data types, HIP types, int8, float8, float8 (E4M3),
+             float8 (E5M2), bfloat8, float16, half, bfloat16, tensorfloat32,
+             float, float32, float64, double, AMD data types, HIP data types,
+             ROCm precision, ROCm data types

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

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

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

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


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

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

 .. image:: ../data/about/compatibility/floating-point-data-types.png
    :alt: Supported floating-point types
@@ -63,43 +67,62 @@ their corresponding HIP type and a short description.
    *
      - float8 (E4M3)
      - ``-``
-      - An 8-bit floating-point number that mostly follows IEEE-754 conventions and **S1E4M3** bit layout, as described in `8-bit Numerical Formats for Deep Neural Networks <https://arxiv.org/abs/2206.02915>`_ , with expanded range and with no infinity or signed zero. NaN is represented as negative zero.
+      - An 8-bit floating-point number that mostly follows IEEE-754 conventions
+        and **S1E4M3** bit layout, as described in `8-bit Numerical Formats for Deep Neural Networks <https://arxiv.org/abs/2206.02915>`_ ,
+        with expanded range and no infinity or signed zero. NaN is
+        represented as negative zero.
    *
      - float8 (E5M2)
      - ``-``
-      - An 8-bit floating-point number mostly following IEEE-754 conventions and **S1E5M2** bit layout, as described in `8-bit Numerical Formats for Deep Neural Networks <https://arxiv.org/abs/2206.02915>`_ , with expanded range and with no infinity or signed zero. NaN is represented as negative zero.
+      - An 8-bit floating-point number mostly following IEEE-754 conventions and
+        **S1E5M2** bit layout, as described in `8-bit Numerical Formats for Deep Neural Networks <https://arxiv.org/abs/2206.02915>`_ ,
+        with expanded range and no infinity or signed zero. NaN is
+        represented as negative zero.
    *
      - float16
      - ``half``
-      - A 16-bit floating-point number that conforms to the IEEE 754-2008 half-precision storage format.
+      - A 16-bit floating-point number that conforms to the IEEE 754-2008
+        half-precision storage format.
    *
      - bfloat16
      - ``bfloat16``
-      - A shortened 16-bit version of the IEEE 754 single-precision storage format.
+      - A shortened 16-bit version of the IEEE 754 single-precision storage
+        format.
    *
      - tensorfloat32
      - ``-``
-      - A floating-point number that occupies 32 bits or less of storage, providing improved range compared to half (16-bit) format, at (potentially) greater throughput than single-precision (32-bit) formats.
+      - A floating-point number that occupies 32 bits or less of storage,
+        providing improved range compared to half (16-bit) format, at
+        (potentially) greater throughput than single-precision (32-bit) formats.
    *
      - float32
      - ``float``
-      - A 32-bit floating-point number that conforms to the IEEE 754 single-precision storage format.
+      - A 32-bit floating-point number that conforms to the IEEE 754
+        single-precision storage format.
    *
      - float64
      - ``double``
-      - A 64-bit floating-point number that conforms to the IEEE 754 double-precision storage format.
+      - A 64-bit floating-point number that conforms to the IEEE 754
+        double-precision storage format.

 .. note::

-  * The float8 and tensorfloat32 types are internal types used in calculations in Matrix Cores and can be stored in any type of the same size.
-  * The encodings for FP8 (E5M2) and FP8 (E4M3) that are natively supported by MI300 differ from the FP8 (E5M2) and FP8 (E4M3) encodings used in H100 (`FP8 Formats for Deep Learning <https://arxiv.org/abs/2209.05433>`_).
+  * The float8 and tensorfloat32 types are internal types used in calculations
+    in Matrix Cores and can be stored in any type of the same size.
+
+  * The encodings for FP8 (E5M2) and FP8 (E4M3) that the
+    MI300 series natively supports differ from the FP8 (E5M2) and FP8 (E4M3)
+    encodings used in NVIDIA H100
+    (`FP8 Formats for Deep Learning <https://arxiv.org/abs/2209.05433>`_).
+
  * In some AMD documents and articles, float8 (E5M2) is referred to as bfloat8.

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

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

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

 .. note::

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

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

-AMD GPU hardware support for data types is listed in the following tables.
+The following tables provide information about AMD Instinct accelerators support
+for various data types. The MI200 series GPUs, which include MI210, MI250, and
+MI250X, are based on the CDNA2 architecture. The MI300 series GPUs, consisting
+of MI300A, MI300X, and MI325X, are built on the CDNA3 architecture.

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

 .. note::

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

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

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

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

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

 .. tab-set::

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

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

 .. tab-set::

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

+
 - caption: Conceptual
  entries:
  - file: conceptual/gpu-arch.md
--- a/docs/sphinx/requirements.in
+++ b/docs/sphinx/requirements.in
@@ -1,3 +1,3 @@
-rocm-docs-core==1.13.0
+rocm-docs-core==1.15.0
 sphinx-reredirects
 sphinx-sitemap
--- a/docs/sphinx/requirements.txt
+++ b/docs/sphinx/requirements.txt
@@ -8,6 +8,13 @@ accessible-pygments==0.0.5
    # via pydata-sphinx-theme
 alabaster==1.0.0
    # via sphinx
+asttokens==3.0.0
+    # via stack-data
+attrs==25.1.0
+    # via
+    #   jsonschema
+    #   jupyter-cache
+    #   referencing
 babel==2.16.0
    # via
    #   pydata-sphinx-theme
@@ -25,9 +32,17 @@ cffi==1.17.1
 charset-normalizer==3.4.0
    # via requests
 click==8.1.7
-    # via sphinx-external-toc
+    # via
+    #   jupyter-cache
+    #   sphinx-external-toc
+comm==0.2.2
+    # via ipykernel
 cryptography==43.0.3
    # via pyjwt
+debugpy==1.8.12
+    # via ipykernel
+decorator==5.1.1
+    # via ipython
 deprecated==1.2.15
    # via pygithub
 docutils==0.21.2
@@ -36,34 +51,103 @@ docutils==0.21.2
    #   myst-parser
    #   pydata-sphinx-theme
    #   sphinx
+exceptiongroup==1.2.2
+    # via ipython
+executing==2.2.0
+    # via stack-data
 fastjsonschema==2.20.0
-    # via rocm-docs-core
+    # via
+    #   nbformat
+    #   rocm-docs-core
 gitdb==4.0.11
    # via gitpython
 gitpython==3.1.43
    # via rocm-docs-core
+greenlet==3.1.1
+    # via sqlalchemy
 idna==3.10
    # via requests
 imagesize==1.4.1
    # via sphinx
+importlib-metadata==8.6.1
+    # via
+    #   jupyter-cache
+    #   myst-nb
+ipykernel==6.29.5
+    # via myst-nb
+ipython==8.31.0
+    # via
+    #   ipykernel
+    #   myst-nb
+jedi==0.19.2
+    # via ipython
 jinja2==3.1.5
    # via
    #   myst-parser
    #   sphinx
+jsonschema==4.23.0
+    # via nbformat
+jsonschema-specifications==2024.10.1
+    # via jsonschema
+jupyter-cache==1.0.1
+    # via myst-nb
+jupyter-client==8.6.3
+    # via
+    #   ipykernel
+    #   nbclient
+jupyter-core==5.7.2
+    # via
+    #   ipykernel
+    #   jupyter-client
+    #   nbclient
+    #   nbformat
 markdown-it-py==3.0.0
    # via
    #   mdit-py-plugins
    #   myst-parser
 markupsafe==3.0.2
    # via jinja2
+matplotlib-inline==0.1.7
+    # via
+    #   ipykernel
+    #   ipython
 mdit-py-plugins==0.4.2
    # via myst-parser
 mdurl==0.1.2
    # via markdown-it-py
-myst-parser==4.0.0
+myst-nb==1.1.2
    # via rocm-docs-core
+myst-parser==4.0.0
+    # via myst-nb
+nbclient==0.10.2
+    # via
+    #   jupyter-cache
+    #   myst-nb
+nbformat==5.10.4
+    # via
+    #   jupyter-cache
+    #   myst-nb
+    #   nbclient
+nest-asyncio==1.6.0
+    # via ipykernel
 packaging==24.2
-    # via sphinx
+    # via
+    #   ipykernel
+    #   sphinx
+parso==0.8.4
+    # via jedi
+pexpect==4.9.0
+    # via ipython
+platformdirs==4.3.6
+    # via jupyter-core
+prompt-toolkit==3.0.50
+    # via ipython
+psutil==6.1.1
+    # via ipykernel
+ptyprocess==0.7.0
+    # via pexpect
+pure-eval==0.2.3
+    # via stack-data
 pycparser==2.22
    # via cffi
 pydata-sphinx-theme==0.16.0
@@ -75,23 +159,42 @@ pygithub==2.5.0
 pygments==2.18.0
    # via
    #   accessible-pygments
+    #   ipython
    #   pydata-sphinx-theme
    #   sphinx
 pyjwt[crypto]==2.10.0
    # via pygithub
 pynacl==1.5.0
    # via pygithub
+python-dateutil==2.9.0.post0
+    # via jupyter-client
 pyyaml==6.0.2
    # via
+    #   jupyter-cache
+    #   myst-nb
    #   myst-parser
    #   rocm-docs-core
    #   sphinx-external-toc
+pyzmq==26.2.0
+    # via
+    #   ipykernel
+    #   jupyter-client
+referencing==0.36.2
+    # via
+    #   jsonschema
+    #   jsonschema-specifications
 requests==2.32.3
    # via
    #   pygithub
    #   sphinx
-rocm-docs-core==1.13.0
+rocm-docs-core==1.15.0
    # via -r requirements.in
+rpds-py==0.22.3
+    # via
+    #   jsonschema
+    #   referencing
+six==1.17.0
+    # via python-dateutil
 smmap==5.0.1
    # via gitdb
 snowballstemmer==2.2.0
@@ -101,6 +204,7 @@ soupsieve==2.6
 sphinx==8.1.3
    # via
    #   breathe
+    #   myst-nb
    #   myst-parser
    #   pydata-sphinx-theme
    #   rocm-docs-core
@@ -137,15 +241,43 @@ sphinxcontrib-qthelp==2.0.0
    # via sphinx
 sphinxcontrib-serializinghtml==2.0.0
    # via sphinx
+sqlalchemy==2.0.37
+    # via jupyter-cache
+stack-data==0.6.3
+    # via ipython
+tabulate==0.9.0
+    # via jupyter-cache
 tomli==2.1.0
    # via sphinx
+tornado==6.4.2
+    # via
+    #   ipykernel
+    #   jupyter-client
+traitlets==5.14.3
+    # via
+    #   comm
+    #   ipykernel
+    #   ipython
+    #   jupyter-client
+    #   jupyter-core
+    #   matplotlib-inline
+    #   nbclient
+    #   nbformat
 typing-extensions==4.12.2
    # via
+    #   ipython
+    #   myst-nb
    #   pydata-sphinx-theme
    #   pygithub
+    #   referencing
+    #   sqlalchemy
 urllib3==2.2.3
    # via
    #   pygithub
    #   requests
+wcwidth==0.2.13
+    # via prompt-toolkit
 wrapt==1.17.0
    # via deprecated
+zipp==3.21.0
+    # via importlib-metadata
Author	SHA1	Message	Date
Istvan Kiss	d946fbeaee	Precision support page update	2025-02-04 15:03:31 +01:00
Daniel Su	7179f2a72f	Ex CI: add REPO_RADEON_VERSION as a global variable, clean up other variables (#4334 )	2025-02-03 16:04:07 -05:00
Daniel Su	0df0f74312	Ex CI: rocprof-sdk & rocprof-systems VCN tracing dependencies (#4332 )	2025-02-03 11:00:52 -05:00
Pratik Basyal	f885b5df6e	Updated ROCm install on Linux installation method link (#4313 )	2025-01-31 16:48:33 -05:00
dependabot[bot]	ee70cb0bb5	Build(deps): Bump rocm-docs-core from 1.13.0 to 1.15.0 in /docs/sphinx (#4315 ) Bumps [rocm-docs-core](https://github.com/ROCm/rocm-docs-core) from 1.13.0 to 1.15.0. - [Release notes](https://github.com/ROCm/rocm-docs-core/releases) - [Changelog](https://github.com/ROCm/rocm-docs-core/blob/develop/CHANGELOG.md) - [Commits](https://github.com/ROCm/rocm-docs-core/compare/v1.13.0...v1.15.0) --- updated-dependencies: - dependency-name: rocm-docs-core dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>	2025-01-29 17:14:55 -07:00
Jeffrey Novotny	d401b5f152	Add ToC and index links to the AI Developer Tutorials (#4312 ) * Add ToC and index links to the AI Developer Tutorials * Change link positioning * Change wording	2025-01-29 14:43:32 -05:00