Footnote update (#4967)

* 6.1.5 compatibility table added

.wordlist.txt

@@ -36,6 +36,7 @@ Bluefield
 Bootloader
 CCD
 CDNA
+CHTML
 CIFAR
 CLI
 CLion
@@ -70,6 +71,7 @@ Concretized
 Conda
 ConnectX
 CuPy
+Dashboarding
 DDR
 DF
 DGEMM
@@ -227,6 +229,7 @@ Mellanox's
 Meta's
 Miniconda
 MirroredStrategy
+Mixtral
 Multicore
 Multithreaded
 MyEnvironment
@@ -272,6 +275,8 @@ OpenMPI
 OpenSSL
 OpenVX
 OpenXLA
+Oversubscription
+PagedAttention
 PCC
 PCI
 PCIe
@@ -293,6 +298,7 @@ PowerShell
 PyPi
 PyTorch
 Qcycles
+Qwen
 RAII
 RAS
 RCCL
@@ -490,6 +496,7 @@ cuLIB
 cuRAND
 cuSOLVER
 cuSPARSE
+customizations
 cTDP
 dataset
 datasets
@@ -561,6 +568,7 @@ hipfort
 hipify
 hipsolver
 hipsparse
+hlist
 hotspotting
 hpc
 hpp
@@ -584,6 +592,7 @@ intra
 invariants
 invocating
 ipo
+jax
 kdb
 kfd
 latencies
@@ -604,6 +613,7 @@ migraphx
 miopen
 miopengemm
 mivisionx
+mjx
 mkdir
 mlirmiopen
 mtypes
@@ -619,6 +629,7 @@ openmp
 openssl
 optimizers
 os
+oversubscription
 pageable
 parallelization
 parameterization
@@ -698,6 +709,7 @@ rocsolver
 rocsparse
 rocthrust
 roctracer
+rst
 runtime
 runtimes
 sL

README.md

@@ -199,4 +199,4 @@ cmake --build build --target=doc
 ## Older ROCm releases
 
 For release information for older ROCm releases, refer to the
-[CHANGELOG](./CHANGELOG.md).
+[ROCm release history](https://rocm.docs.amd.com/en/latest/release/versions.html).

RELEASE.md

@@ -80,14 +80,16 @@ The [ROCm Offline Installer Creator 6.2.1](https://rocm.docs.amd.com/projects/in
 
 #### ROCm documentation changes 
 
-There have been no changes to supported hardware or operating systems from ROCm 6.2.0 to ROCm 6.2.1.
+The HIP documentation has been updated with several new topics aimed at improving usability
+and providing more detailed information.
 
 * The Programming Model Reference and Understanding the Programming Model topics in HIP have been consolidated into one topic,
 [HIP programming model (conceptual)](https://rocm.docs.amd.com/projects/HIP/en/docs-6.2.1/understand/programming_model.html). 
+
 * The [HIP virtual memory management](https://rocm.docs.amd.com/projects/HIP/en/docs-6.2.1/how-to/virtual_memory.html) and [HIP virtual memory management API](https://rocm.docs.amd.com/projects/HIP/en/docs-6.2.1/reference/virtual_memory_reference.html) topics have been added.
 
 ```{note}
-The ROCm documentation, like all ROCm projects, is open source and available on GitHub. To contribute to ROCm documentation, see the [ROCm documentation contribution guidelines](https://rocm.docs.amd.com/en/latest/contribute/contributing.html).
+To contribute to ROCm documentation, see the [ROCm documentation contribution guidelines](https://rocm.docs.amd.com/en/latest/contribute/contributing.html).
 ```
 
 ### Operating system and hardware support changes
@@ -324,7 +326,7 @@ Click the component's updated version to go to a detailed list of its changes. C
             </tr>
             <tr>
                 <td><a href="https://rocm.docs.amd.com/projects/rdc/en/docs-6.2.1">ROCm Data Center Tool</a></td>
-                <td>1.0.0</td>
+                <td>0.3.0</td>
                 <td><a href="https://github.com/ROCm/rdc/releases/tag/rocm-6.2.1"><i
                             class="fab fa-github fa-lg"></i></a></td>
             </tr>

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

@@ -1,117 +1,117 @@
-ROCm Version,6.2.2,6.2.1,6.2.0, 6.1.2, 6.1.1, 6.1.0, 6.0.2, 6.0.0
-      :ref:`Operating systems & kernels <OS-kernel-versions>`,"Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04",Ubuntu 24.04,,,,,
-      ,"Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3, 22.04.2","Ubuntu 22.04.4, 22.04.3, 22.04.2"
-      ,,,,"Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5"
-      ,"RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4 [#red-hat94-past-60]_, 9.3, 9.2","RHEL 9.4 [#red-hat94-past-60]_, 9.3, 9.2","RHEL 9.4 [#red-hat94-past-60]_, 9.3, 9.2","RHEL 9.3, 9.2","RHEL 9.3, 9.2"
-      ,"RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8"
-      ,"SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4"
-      ,,,,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9
-      ,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,,,
-      ,.. _architecture-support-compatibility-matrix-past-60:,,,,,,,
-      :doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3
-      ,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2
-      ,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA
-      ,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3
-      ,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2
-      ,.. _gpu-support-compatibility-matrix-past-60:,,,,,,,
-      :doc:`GPU / LLVM target <rocm-install-on-linux:reference/system-requirements>`,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100
-      ,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030
-      ,gfx942 [#mi300_622-past-60]_,gfx942 [#mi300_621-past-60]_,gfx942 [#mi300_620-past-60]_, gfx942 [#mi300_612-past-60]_, gfx942 [#mi300_611-past-60]_, gfx942 [#mi300_610-past-60]_, gfx942 [#mi300_602-past-60]_, gfx942 [#mi300_600-past-60]_
-      ,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a
-      ,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908
-      ,,,,,,,,
-      FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix-past-60:,,,,,,,
-      :doc:`PyTorch <rocm-install-on-linux:install/3rd-party/pytorch-install>`,"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"
-      :doc:`TensorFlow <rocm-install-on-linux:install/3rd-party/tensorflow-install>`,"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","2.14.0, 2.13.1, 2.12.1","2.14.0, 2.13.1, 2.12.1"
-      :doc:`JAX <rocm-install-on-linux:install/3rd-party/jax-install>`,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
-      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
-      ,,,,,,,,
-      THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix-past-60:,,,,,,,
-      `UCC <https://github.com/ROCm/ucc>`_,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.2.0,>=1.2.0
-      `UCX <https://github.com/ROCm/ucx>`_,>=1.15.0,>=1.15.0,>=1.15.0,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1
-      ,,,,,,,,
-      THIRD PARTY ALGORITHM,.. _thirdpartyalgorithm-support-compatibility-matrix-past-60:,,,,,,,
-      Thrust,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
-      CUB,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
-      ,,,,,,,,
-      KFD & USER SPACE [#kfd_support-past-60]_,.. _kfd-userspace-support-compatibility-matrix-past-60:,,,,,,,
-      Tested user space versions,"6.1.x, 6.0.x","6.1.x, 6.0.x","6.1.x, 6.0.x","6.2.x, 6.0.x, 5.7.x","6.2.x, 6.0.x, 5.7.x","6.2.x, 6.0.x, 5.7.x","6.2.x, 6.0.x, 5.7.x, 5.6.x","6.2.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
-      :doc:`MIGraphX <amdmigraphx:index>`,2.10.0,2.10.0,2.10.0,2.9.0,2.9.0,2.9.0,2.8.0,2.8.0
-      :doc:`MIOpen <miopen:index>`,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
-      :doc:`MIVisionX <mivisionx:index>`,3.0.0,3.0.0,3.0.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0
-      :doc:`rocAL <rocal:index>`,2.0.0,2.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
-      :doc:`rocDecode <rocdecode:index>`,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,N/A,N/A
-      :doc:`rocPyDecode <rocpydecode:index>`,0.1.0,0.1.0,0.1.0,N/A,N/A,N/A,N/A,N/A
-      :doc:`RPP <rpp:index>`,1.8.0,1.8.0,1.8.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0
-      ,,,,,,,,
-      COMMUNICATION,.. _commlibs-support-compatibility-matrix-past-60:,,,,,,,
-      :doc:`RCCL <rccl:index>`,2.20.5,2.20.5,2.20.5,2.18.6,2.18.6,2.18.6,2.18.3,2.18.3
-      ,,,,,,,,
-      MATH LIBS,.. _mathlibs-support-compatibility-matrix-past-60:,,,,,,,
-      `half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0
-      :doc:`hipBLAS <hipblas:index>`,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0
-      :doc:`hipBLASLt <hipblaslt:index>`,0.8.0,0.8.0,0.8.0,0.7.0,0.7.0,0.7.0,0.6.0,0.6.0
-      :doc:`hipFFT <hipfft:index>`,1.0.15,1.0.15,1.0.14,1.0.14,1.0.14,1.0.14,1.0.13,1.0.13
-      :doc:`hipFORT <hipfort:index>`,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0
-      :doc:`hipRAND <hiprand:index>`,2.11.0,2.11.0,2.11.0,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16
-      :doc:`hipSOLVER <hipsolver:index>`,2.2.0,2.2.0,2.2.0,2.1.1,2.1.1,2.1.0,2.0.0,2.0.0
-      :doc:`hipSPARSE <hipsparse:index>`,3.1.1,3.1.1,3.1.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
-      :doc:`hipSPARSELt <hipsparselt:index>`,0.2.1,0.2.1,0.2.1,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0
-      :doc:`rocALUTION <rocalution:index>`,3.2.0,3.2.0,3.2.0,3.1.1,3.1.1,3.1.1,3.0.3,3.0.3
-      :doc:`rocBLAS <rocblas:index>`,4.2.1,4.2.1,4.2.0,4.1.2,4.1.0,4.1.0,4.0.0,4.0.0
-      :doc:`rocFFT <rocfft:index>`,1.0.29,1.0.29,1.0.28,1.0.27,1.0.27,1.0.26,1.0.25,1.0.23
-      :doc:`rocRAND <rocrand:index>`,3.1.0,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.0,2.10.17
-      :doc:`rocSOLVER <rocsolver:index>`,3.26.0,3.26.0,3.26.0,3.25.0,3.25.0,3.25.0,3.24.0,3.24.0
-      :doc:`rocSPARSE <rocsparse:index>`,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.0.2,3.0.2
-      :doc:`rocWMMA <rocwmma:index>`,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0
-      `Tensile <https://github.com/ROCm/Tensile>`_,4.40.0,4.40.0,4.40.0,4.40.0,4.40.0,4.40.0,4.39.0,4.39.0
-      ,,,,,,,,
-      PRIMITIVES,.. _primitivelibs-support-compatibility-matrix-past-60:,,,,,,,
-      :doc:`hipCUB <hipcub:index>`,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
-      :doc:`hipTensor <hiptensor:index>`,1.3.0,1.3.0,1.3.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0
-      :doc:`rocPRIM <rocprim:index>`,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
-      :doc:`rocThrust <rocthrust:index>`,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
-      ,,,,,,,,
-      SUPPORT LIBS,,,,,,,,
-      `hipother <https://github.com/ROCm/hipother>`_,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
-      `rocm-core <https://github.com/ROCm/rocm-core>`_,6.2.2,6.2.1,6.2.0,6.1.2,6.1.1,6.1.0,6.0.2,6.0.0
-      `ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,20240607.4.05,20240607.4.05,20240607.1.4246,20240125.5.08,20240125.5.08,20240125.3.30,20231016.2.245,20231016.2.245
-      ,,,,,,,,
-      SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix-past-60:,,,,,,,
-      :doc:`AMD SMI <amdsmi:index>`,24.6.3,24.6.3,24.6.2,24.5.1,24.5.1,24.4.1,23.4.2,23.4.2
-      :doc:`ROCm Data Center Tool <rdc:index>`,1.0.0,1.0.0,1.0.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0
-      :doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
-      :doc:`ROCm SMI <rocm_smi_lib:index>`,7.3.0,7.3.0,7.3.0,7.2.0,7.0.0,7.0.0,6.0.2,6.0.0
-      :doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,rocm-6.2.2,rocm-6.2.1,rocm-6.2.0,rocm-6.1.2,rocm-6.1.1,rocm-6.1.0,rocm-6.0.2,rocm-6.0.0
-      ,,,,,,,,
-      PERFORMANCE TOOLS,,,,,,,,
-      :doc:`Omniperf <omniperf:index>`,2.0.1,2.0.1,2.0.1,N/A,N/A,N/A,N/A,N/A
-      :doc:`Omnitrace <omnitrace:index>`,1.11.2,1.11.2,1.11.2,N/A,N/A,N/A,N/A,N/A
-      :doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0
-      :doc:`ROCProfiler <rocprofiler:index>`,2.0.60202,2.0.60201,2.0.60200,2.0.60102,2.0.60101,2.0.60100,2.0.60002,2.0.60000
-      :doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,0.4.0,0.4.0,0.4.0,N/A,N/A,N/A,N/A,N/A
-      :doc:`ROCTracer <roctracer:index>`,4.1.60202,4.1.60201,4.1.60200,4.1.60102,4.1.60101,4.1.60100,4.1.60002,4.1.60000
-      ,,,,,,,,
-      DEVELOPMENT TOOLS,,,,,,,,
-      :doc:`HIPIFY <hipify:index>`,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-      :doc:`ROCm CMake <rocmcmakebuildtools:index>`,0.13.0,0.13.0,0.13.0,0.12.0,0.12.0,0.12.0,0.11.0,0.11.0
-      :doc:`ROCdbgapi <rocdbgapi:index>`,0.76.0,0.76.0,0.76.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0
-      :doc:`ROCm Debugger (ROCgdb) <rocgdb:index>`,14.2.0,14.2.0,14.2.0,14.1.0,14.1.0,14.1.0,13.2.0,13.2.0
-      `rocprofiler-register <https://github.com/ROCm/rocprofiler-register>`_,0.4.0,0.4.0,0.4.0,0.3.0,0.3.0,0.3.0,N/A,N/A
-      :doc:`ROCr Debug Agent <rocr_debug_agent:index>`,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3
-      ,,,,,,,,
-      COMPILERS,.. _compilers-support-compatibility-matrix-past-60:,,,,,,,
-      `clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0
-      :doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
-      `Flang <https://github.com/ROCm/flang>`_,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-      :doc:`llvm-project <llvm-project:index>`,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-      `OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
-      ,,,,,,,,
-      RUNTIMES,.. _runtime-support-compatibility-matrix-past-60:,,,,,,,
-      :doc:`AMD CLR <hip:understand/amd_clr>`,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
-      :doc:`HIP <hip:index>`,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
-      `OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0
-      :doc:`ROCR-Runtime <rocr-runtime:index>`,1.14.0,1.14.0,1.13.0,1.13.0,1.13.0,1.13.0,1.12.0,1.12.0
+ROCm Version,6.2.2,6.2.1,6.2.0, 6.1.5, 6.1.2, 6.1.1, 6.1.0, 6.0.2, 6.0.0
+      :ref:`Operating systems & kernels <OS-kernel-versions>`,"Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04",Ubuntu 24.04,,,,,,
+      ,"Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4","Ubuntu 22.04.5, 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3","Ubuntu 22.04.4, 22.04.3, 22.04.2","Ubuntu 22.04.4, 22.04.3, 22.04.2"
+      ,,,,"Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5","Ubuntu 20.04.6, 20.04.5"
+      ,"RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4 [#red-hat94-past-60]_, 9.3, 9.2","RHEL 9.4 [#red-hat94-past-60]_, 9.3, 9.2","RHEL 9.4 [#red-hat94-past-60]_, 9.3, 9.2","RHEL 9.4 [#red-hat94-past-60]_, 9.3, 9.2","RHEL 9.3, 9.2","RHEL 9.3, 9.2"
+      ,"RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.10, 8.9","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8","RHEL 8.9, 8.8"
+      ,"SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4","SLES 15 SP5, SP4"
+      ,,,,,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9,CentOS 7.9
+      ,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,Oracle Linux 8.9 [#oracle89-past-60]_,,,
+      ,.. _architecture-support-compatibility-matrix-past-60:,,,,,,,,
+      :doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3
+      ,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2
+      ,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA
+      ,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3
+      ,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2
+      ,.. _gpu-support-compatibility-matrix-past-60:,,,,,,,,
+      :doc:`GPU / LLVM target <rocm-install-on-linux:reference/system-requirements>`,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100
+      ,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030
+      ,gfx942 [#mi300_622-past-60]_,gfx942 [#mi300_621-past-60]_,gfx942 [#mi300_620-past-60]_, gfx942 [#mi300_612-past-60]_, gfx942 [#mi300_612-past-60]_, gfx942 [#mi300_611-past-60]_, gfx942 [#mi300_610-past-60]_, gfx942 [#mi300_602-past-60]_, gfx942 [#mi300_600-past-60]_
+      ,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a
+      ,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908
+      ,,,,,,,,,
+      FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix-past-60:,,,,,,,,
+      :doc:`PyTorch <rocm-install-on-linux:install/3rd-party/pytorch-install>`,"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 <rocm-install-on-linux:install/3rd-party/tensorflow-install>`,"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 <rocm-install-on-linux:install/3rd-party/jax-install>`,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
+      `ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
+      ,,,,,,,,,
+      THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix-past-60:,,,,,,,,
+      `UCC <https://github.com/ROCm/ucc>`_,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.2.0,>=1.2.0
+      `UCX <https://github.com/ROCm/ucx>`_,>=1.15.0,>=1.15.0,>=1.15.0,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1,>=1.14.1
+      ,,,,,,,,,
+      THIRD PARTY ALGORITHM,.. _thirdpartyalgorithm-support-compatibility-matrix-past-60:,,,,,,,,
+      Thrust,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
+      CUB,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
+      ,,,,,,,,,
+      KFD & USER SPACE [#kfd_support-past-60]_,.. _kfd-userspace-support-compatibility-matrix-past-60:,,,,,,,,
+      Tested user space versions,"6.1.x, 6.0.x","6.1.x, 6.0.x","6.1.x, 6.0.x","6.2.x, 6.0.x, 5.7.x","6.2.x, 6.0.x, 5.7.x","6.2.x, 6.0.x, 5.7.x","6.2.x, 6.0.x, 5.7.x","6.2.x, 6.0.x, 5.7.x, 5.6.x","6.2.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
+      :doc:`MIGraphX <amdmigraphx:index>`,2.10.0,2.10.0,2.10.0,2.9.0,2.9.0,2.9.0,2.9.0,2.8.0,2.8.0
+      :doc:`MIOpen <miopen:index>`,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
+      :doc:`MIVisionX <mivisionx:index>`,3.0.0,3.0.0,3.0.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0
+      :doc:`rocAL <rocal:index>`,2.0.0,2.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
+      :doc:`rocDecode <rocdecode:index>`,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,N/A,N/A
+      :doc:`rocPyDecode <rocpydecode:index>`,0.1.0,0.1.0,0.1.0,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`RPP <rpp:index>`,1.8.0,1.8.0,1.8.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0
+      ,,,,,,,,,
+      COMMUNICATION,.. _commlibs-support-compatibility-matrix-past-60:,,,,,,,,
+      :doc:`RCCL <rccl:index>`,2.20.5,2.20.5,2.20.5,2.18.6,2.18.6,2.18.6,2.18.6,2.18.3,2.18.3
+      ,,,,,,,,,
+      MATH LIBS,.. _mathlibs-support-compatibility-matrix-past-60:,,,,,,,,
+      `half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0
+      :doc:`hipBLAS <hipblas:index>`,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0
+      :doc:`hipBLASLt <hipblaslt:index>`,0.8.0,0.8.0,0.8.0,0.7.0,0.7.0,0.7.0,0.7.0,0.6.0,0.6.0
+      :doc:`hipFFT <hipfft:index>`,1.0.15,1.0.15,1.0.14,1.0.14,1.0.14,1.0.14,1.0.14,1.0.13,1.0.13
+      :doc:`hipFORT <hipfort:index>`,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0
+      :doc:`hipRAND <hiprand:index>`,2.11.0,2.11.0,2.11.0,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16
+      :doc:`hipSOLVER <hipsolver:index>`,2.2.0,2.2.0,2.2.0,2.1.1,2.1.1,2.1.1,2.1.0,2.0.0,2.0.0
+      :doc:`hipSPARSE <hipsparse:index>`,3.1.1,3.1.1,3.1.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
+      :doc:`hipSPARSELt <hipsparselt:index>`,0.2.1,0.2.1,0.2.1,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0
+      :doc:`rocALUTION <rocalution:index>`,3.2.0,3.2.0,3.2.0,3.1.1,3.1.1,3.1.1,3.1.1,3.0.3,3.0.3
+      :doc:`rocBLAS <rocblas:index>`,4.2.1,4.2.1,4.2.0,4.1.2,4.1.2,4.1.0,4.1.0,4.0.0,4.0.0
+      :doc:`rocFFT <rocfft:index>`,1.0.29,1.0.29,1.0.28,1.0.27,1.0.27,1.0.27,1.0.26,1.0.25,1.0.23
+      :doc:`rocRAND <rocrand:index>`,3.1.0,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,2.10.17
+      :doc:`rocSOLVER <rocsolver:index>`,3.26.0,3.26.0,3.26.0,3.25.0,3.25.0,3.25.0,3.25.0,3.24.0,3.24.0
+      :doc:`rocSPARSE <rocsparse:index>`,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.0.2,3.0.2
+      :doc:`rocWMMA <rocwmma:index>`,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0
+      `Tensile <https://github.com/ROCm/Tensile>`_,4.40.0,4.40.0,4.40.0,4.40.0,4.40.0,4.40.0,4.40.0,4.39.0,4.39.0
+      ,,,,,,,,,
+      PRIMITIVES,.. _primitivelibs-support-compatibility-matrix-past-60:,,,,,,,,
+      :doc:`hipCUB <hipcub:index>`,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
+      :doc:`hipTensor <hiptensor:index>`,1.3.0,1.3.0,1.3.0,1.2.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0
+      :doc:`rocPRIM <rocprim:index>`,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
+      :doc:`rocThrust <rocthrust:index>`,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
+      ,,,,,,,,,
+      SUPPORT LIBS,,,,,,,,,
+      `hipother <https://github.com/ROCm/hipother>`_,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
+      `rocm-core <https://github.com/ROCm/rocm-core>`_,6.2.2,6.2.1,6.2.0,6.1.5,6.1.2,6.1.1,6.1.0,6.0.2,6.0.0
+      `ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,20240607.4.05,20240607.4.05,20240607.1.4246,20240125.5.08,20240125.5.08,20240125.5.08,20240125.3.30,20231016.2.245,20231016.2.245
+      ,,,,,,,,,
+      SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix-past-60:,,,,,,,,
+      :doc:`AMD SMI <amdsmi:index>`,24.6.3,24.6.3,24.6.2,24.5.1,24.5.1,24.5.1,24.4.1,23.4.2,23.4.2
+      :doc:`ROCm Data Center Tool <rdc:index>`,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0
+      :doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
+      :doc:`ROCm SMI <rocm_smi_lib:index>`,7.3.0,7.3.0,7.3.0,7.2.0,7.2.0,7.0.0,7.0.0,6.0.2,6.0.0
+      :doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,rocm-6.2.2,rocm-6.2.1,rocm-6.2.0,rocm-6.1.5,rocm-6.1.2,rocm-6.1.1,rocm-6.1.0,rocm-6.0.2,rocm-6.0.0
+      ,,,,,,,,,
+      PERFORMANCE TOOLS,,,,,,,,,
+      :doc:`Omniperf <omniperf:index>`,2.0.1,2.0.1,2.0.1,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`Omnitrace <omnitrace:index>`,1.11.2,1.11.2,1.11.2,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0
+      :doc:`ROCProfiler <rocprofiler:index>`,2.0.60202,2.0.60201,2.0.60200,2.0.60105,2.0.60102,2.0.60101,2.0.60100,2.0.60002,2.0.60000
+      :doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,0.4.0,0.4.0,0.4.0,N/A,N/A,N/A,N/A,N/A,N/A
+      :doc:`ROCTracer <roctracer:index>`,4.1.60202,4.1.60201,4.1.60200,4.1.60105,4.1.60102,4.1.60101,4.1.60100,4.1.60002,4.1.60000
+      ,,,,,,,,,
+      DEVELOPMENT TOOLS,,,,,,,,,
+      :doc:`HIPIFY <hipify:index>`,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+      :doc:`ROCm CMake <rocmcmakebuildtools:index>`,0.13.0,0.13.0,0.13.0,0.12.0,0.12.0,0.12.0,0.12.0,0.11.0,0.11.0
+      :doc:`ROCdbgapi <rocdbgapi:index>`,0.76.0,0.76.0,0.76.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0
+      :doc:`ROCm Debugger (ROCgdb) <rocgdb:index>`,14.2.0,14.2.0,14.2.0,14.1.0,14.1.0,14.1.0,14.1.0,13.2.0,13.2.0
+      `rocprofiler-register <https://github.com/ROCm/rocprofiler-register>`_,0.4.0,0.4.0,0.4.0,0.3.0,0.3.0,0.3.0,0.3.0,N/A,N/A
+      :doc:`ROCr Debug Agent <rocr_debug_agent:index>`,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3
+      ,,,,,,,,,
+      COMPILERS,.. _compilers-support-compatibility-matrix-past-60:,,,,,,,,
+      `clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0
+      :doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
+      `Flang <https://github.com/ROCm/flang>`_,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+      :doc:`llvm-project <llvm-project:index>`,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+      `OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
+      ,,,,,,,,,
+      RUNTIMES,.. _runtime-support-compatibility-matrix-past-60:,,,,,,,,
+      :doc:`AMD CLR <hip:understand/amd_clr>`,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
+      :doc:`HIP <hip:index>`,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
+      `OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0
+      :doc:`ROCR-Runtime <rocr-runtime:index>`,1.14.0,1.14.0,1.13.0,1.13.0,1.13.0,1.13.0,1.13.0,1.12.0,1.12.0

docs/compatibility/compatibility-matrix.rst

@@ -10,6 +10,8 @@ Use this matrix to view the ROCm compatibility and system requirements across su
 
 You can also refer to the :ref:`past versions of ROCm compatibility matrix<past-rocm-compatibility-matrix>`.
 
+Accelerators and GPUs listed in the following table support compute workloads (no display information or graphics). If you’re using ROCm with AMD Radeon or Radeon Pro GPUs for graphics workloads, see the `Use ROCm on Radeon GPU documentation <https://rocm.docs.amd.com/projects/radeon/en/latest/docs/compatibility.html>`_ to verify compatibility and system requirements.
+
 .. |br| raw:: html
 
    <br/>
@@ -103,7 +105,7 @@ You can also refer to the :ref:`past versions of ROCm compatibility matrix<past-
       ,,,
       SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix:,,
       :doc:`AMD SMI <amdsmi:index>`,24.6.3,24.6.3,24.4.1
-      :doc:`ROCm Data Center Tool <rdc:index>`,1.0.0,1.0.0,0.3.0
+      :doc:`ROCm Data Center Tool <rdc:index>`,0.3.0,0.3.0,0.3.0
       :doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0
       :doc:`ROCm SMI <rocm_smi_lib:index>`,7.3.0,7.3.0,7.0.0
       :doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,rocm-6.2.2,rocm-6.2.1,rocm-6.1.0
@@ -145,7 +147,7 @@ You can also refer to the :ref:`past versions of ROCm compatibility matrix<past-
 .. [#mi300_622] **For ROCm 6.2.2** - MI300X (gfx942) is supported on listed operating systems *except* Ubuntu 22.04.5 [6.8 HWE] and Ubuntu 22.04.4 [6.5 HWE].
 .. [#mi300_621] **For ROCm 6.2.1** - MI300X (gfx942) is supported on listed operating systems *except* Ubuntu 22.04.5 [6.8 HWE] and Ubuntu 22.04.4 [6.5 HWE].
 .. [#mi300_610] **For ROCm 6.1.0** - MI300A (gfx942) is supported on Ubuntu 22.04.4, RHEL 9.4, RHEL 9.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.4.
-.. [#kfd_support] ROCm provides forward and backward compatibility between the Kernel Fusion Driver (KFD) and its user space software for +/- 2 releases. These are the compatibility combinations that are currently supported.
+.. [#kfd_support] ROCm provides forward and backward compatibility between the Kernel Fusion Driver (KFD) and its user space software for +/- 2 releases. The tested user space versions on this page were accurate as of the time of initial ROCm release. For the most up-to-date information, see the latest version of this information at `User and kernel-space support matrix <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/user-kernel-space-compat-matrix.html>`_.
 
 
 .. _OS-kernel-versions:
@@ -222,4 +224,4 @@ Expand for full historical view of:
    .. [#mi300_610-past-60] **For ROCm 6.1.0** - MI300A (gfx942) is supported on Ubuntu 22.04.4, RHEL 9.4, RHEL 9.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.4.
    .. [#mi300_602-past-60] **For ROCm 6.0.2** - MI300A (gfx942) is supported on Ubuntu 22.04.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.3.
    .. [#mi300_600-past-60] **For ROCm 6.0.0** - MI300A (gfx942) is supported on Ubuntu 22.04.3, RHEL 8.9, and SLES 15 SP5. MI300X (gfx942) is only supported on Ubuntu 22.04.3.
-   .. [#kfd_support-past-60] ROCm provides forward and backward compatibility between the Kernel Fusion Driver (KFD) and its user space software for +/- 2 releases. These are the compatibility combinations that are currently supported.
+   .. [#kfd_support-past-60] ROCm provides forward and backward compatibility between the Kernel Fusion Driver (KFD) and its user space software for +/- 2 releases. The tested user space versions on this page were accurate as of the time of initial ROCm release. For the most up-to-date information, see the latest version of this information at `User and kernel-space support matrix <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/reference/user-kernel-space-compat-matrix.html>`_.

docs/conceptual/ai-migraphx-optimization.md

@@ -1,333 +0,0 @@
-<head>
-  <meta charset="UTF-8">
-  <meta name="description" content="Inference optimization with MIGraphX">
-  <meta name="keywords" content="Inference optimization, MIGraphX, deep-learning, MIGraphX
-  installation, AMD, ROCm">
-</head>
-
-# Inference optimization with MIGraphX
-
-The following sections cover inferencing and introduces [MIGraphX](https://rocm.docs.amd.com/projects/AMDMIGraphX/en/latest/).
-
-## Inference
-
-The inference is where capabilities learned during deep-learning training are put to work. It refers to using a fully trained neural network to make conclusions (predictions) on unseen data that the model has never interacted with before. Deep-learning inferencing is achieved by feeding new data, such as new images, to the network, giving the Deep Neural Network a chance to classify the image.
-
-Taking our previous example of MNIST, the DNN can be fed new images of handwritten digit images, allowing the neural network to classify digits. A fully trained DNN should make accurate predictions about what an image represents, and inference cannot happen without training.
-
-## MIGraphX introduction
-
-MIGraphX is a graph compiler focused on accelerating the machine-learning inference that can target AMD GPUs and CPUs. MIGraphX accelerates the machine-learning models by leveraging several graph-level transformations and optimizations. These optimizations include:
-
-* Operator fusion
-* Arithmetic simplifications
-* Dead-code elimination
-* Common subexpression elimination (CSE)
-* Constant propagation
-
-After doing all these transformations, MIGraphX emits code for the AMD GPU by calling to MIOpen or rocBLAS or creating HIP kernels for a particular operator. MIGraphX can also target CPUs using DNNL or ZenDNN libraries.
-
-MIGraphX provides easy-to-use APIs in C++ and Python to import machine models in ONNX or TensorFlow. Users can compile, save, load, and run these models using the MIGraphX C++ and Python APIs. Internally, MIGraphX parses ONNX or TensorFlow models into internal graph representation where each operator in the model gets mapped to an operator within MIGraphX. Each of these operators defines various attributes such as:
-
-* Number of arguments
-* Type of arguments
-* Shape of arguments
-
-After optimization passes, all these operators get mapped to different kernels on GPUs or CPUs.
-
-After importing a model into MIGraphX, the model is represented as `migraphx::program`. `migraphx::program` is made up of `migraphx::module`. The program can consist of several modules, but it always has one main_module. Modules are made up of `migraphx::instruction_ref`. Instructions contain the `migraphx::op` and arguments to the operator.  
-
-## Installing MIGraphX
-
-There are three options to get started with MIGraphX installation. MIGraphX depends on ROCm libraries; assume that the machine has ROCm installed.
-
-### Option 1: installing binaries
-
-To install MIGraphX on Debian-based systems like Ubuntu, use the following command:
-
-```bash
-sudo apt update && sudo apt install -y migraphx
-```
-
-The header files and libraries are installed under `/opt/rocm-\<version\>`, where \<version\> is the ROCm version.
-
-### Option 2: building from source
-
-There are two ways to build the MIGraphX sources.
-
-* [Use the ROCm build tool](https://github.com/ROCm/AMDMIGraphX#use-the-rocm-build-tool-rbuild) - This approach uses `[rbuild](https://github.com/ROCm/rbuild)` to install the prerequisites and build the libraries with just one command.
-
-  or
-
-* [Use CMake](https://github.com/ROCm/AMDMIGraphX#use-cmake-to-build-migraphx) - This approach uses a script to install the prerequisites, then uses CMake to build the source.
-
-For detailed steps on building from source and installing dependencies, refer to the following `README` file:
-
-[https://github.com/ROCm/AMDMIGraphX#building-from-source](https://github.com/ROCm/AMDMIGraphX#building-from-source)
-
-### Option 3: use docker
-
-To use Docker, follow these steps:
-
-1. The easiest way to set up the development environment is to use Docker. To build Docker from scratch, first clone the MIGraphX repository by running:
-
-    ```bash
-    git clone --recursive https://github.com/ROCm/AMDMIGraphX
-    ```
-
-2. The repository contains a Dockerfile from which you can build a Docker image as:
-
-    ```bash
-    docker build -t migraphx .
-    ```
-
-3. Then to enter the development environment, use Docker run:
-
-    ```bash
-    docker run --device='/dev/kfd' --device='/dev/dri' -v=`pwd`:/code/AMDMIGraphX -w /code/AMDMIGraphX --group-add video -it migraphx
-    ```
-
-The Docker image contains all the prerequisites required for the installation, so users can go to the folder `/code/AMDMIGraphX` and follow the steps mentioned in [Option 2: Building from Source](#option-2-building-from-source).
-
-## MIGraphX example
-
-MIGraphX provides both C++ and Python APIs. The following sections show examples of both using the Inception v3 model. To walk through the examples, fetch the Inception v3 ONNX model by running the following:
-
-```py
-import torch
-import torchvision.models as models
-inception = models.inception_v3(pretrained=True)
-torch.onnx.export(inception,torch.randn(1,3,299,299), "inceptioni1.onnx")
-```
-
-This will create `inceptioni1.onnx`, which can be imported in MIGraphX using C++ or Python API.
-
-### MIGraphX Python API
-
-Follow these steps:
-
-1. To import the MIGraphX module in Python script, set `PYTHONPATH` to the MIGraphX libraries installation. If binaries are installed using steps mentioned in [Option 1: Installing Binaries](#option-1-installing-binaries), perform the following action:
-
-    ```bash
-    export PYTHONPATH=$PYTHONPATH:/opt/rocm/
-    ```
-
-2. The following script shows the usage of Python API to import the ONNX model, compile it, and run inference on it. Set `LD_LIBRARY_PATH` to `/opt/rocm/` if required.
-
-    ```py
-    # import migraphx and numpy
-    import migraphx
-    import numpy as np
-    # import and parse inception model
-    model = migraphx.parse_onnx("inceptioni1.onnx")
-    # compile model for the GPU target
-    model.compile(migraphx.get_target("gpu"))
-    # optionally print compiled model
-    model.print()
-    # create random input image
-    input_image = np.random.rand(1, 3, 299, 299).astype('float32')
-    # feed image to model, 'x.1` is the input param name
-    results = model.run({'x.1': input_image})
-    # get the results back
-    result_np = np.array(results[0])
-    # print the inferred class of the input image
-    print(np.argmax(result_np))
-    ```
-
-    Find additional examples of Python API in the `/examples` directory of the MIGraphX repository.
-
-## MIGraphX C++ API
-
-Follow these steps:
-
-1. The following is a minimalist example that shows the usage of MIGraphX C++ API to load ONNX file, compile it for the GPU, and run inference on it. To use MIGraphX C++ API, you only need to load the `migraphx.hpp` file. This example runs inference on the Inception v3 model.
-
-    ```c++
-    #include <vector>
-    #include <string>
-    #include <algorithm>
-    #include <ctime>
-    #include <random>
-    #include <migraphx/migraphx.hpp>
-
-    int main(int argc, char** argv)
-    {
-        migraphx::program prog;
-        migraphx::onnx_options onnx_opts;
-        // import and parse onnx file into migraphx::program
-        prog = parse_onnx("inceptioni1.onnx", onnx_opts);
-        // print imported model
-        prog.print();
-        migraphx::target targ = migraphx::target("gpu");
-        migraphx::compile_options comp_opts;
-        comp_opts.set_offload_copy();
-        // compile for the GPU
-        prog.compile(targ, comp_opts);
-        // print the compiled program
-        prog.print();
-        // randomly generate input image
-        // of shape (1, 3, 299, 299)
-        std::srand(unsigned(std::time(nullptr)));
-        std::vector<float> input_image(1*299*299*3);
-        std::generate(input_image.begin(), input_image.end(), std::rand);
-        // users need to provide data for the input
-        // parameters in order to run inference
-        // you can query into migraph program for the parameters
-        migraphx::program_parameters prog_params;
-        auto param_shapes = prog.get_parameter_shapes();
-        auto input        = param_shapes.names().front();
-        // create argument for the parameter
-        prog_params.add(input, migraphx::argument(param_shapes[input], input_image.data()));
-        // run inference
-        auto outputs = prog.eval(prog_params);
-        // read back the output
-        float* results = reinterpret_cast<float*>(outputs[0].data());
-        float* max     = std::max_element(results, results + 1000);
-        int answer = max - results;
-        std::cout << "answer: " << answer << std::endl;
-    }
-    ```
-
-2. To compile this program, you can use CMake and you only need to link the `migraphx::c` library to use MIGraphX's C++ API. The following is the `CMakeLists.txt` file that can build the earlier example:
-
-    ```cmake
-    cmake_minimum_required(VERSION 3.5)
-    project (CAI)
-
-    set (CMAKE_CXX_STANDARD 14)
-    set (EXAMPLE inception_inference)
-
-    list (APPEND CMAKE_PREFIX_PATH /opt/rocm/hip /opt/rocm)
-    find_package (migraphx)
-
-    message("source file: " ${EXAMPLE}.cpp " ---> bin: " ${EXAMPLE})
-    add_executable(${EXAMPLE} ${EXAMPLE}.cpp)
-
-    target_link_libraries(${EXAMPLE} migraphx::c)
-    ```
-
-3. To build the executable file, run the following from the directory containing the `inception_inference.cpp` file:
-
-    ```bash
-    mkdir build
-    cd build
-    cmake ..
-    make -j$(nproc)
-    ./inception_inference
-    ```
-
-:::{note}
-    Set `LD_LIBRARY_PATH` to `/opt/rocm/lib` if required during the build. Additional examples can be found in the MIGraphX repository under the `/examples/` directory.
-:::
-
-## Tuning MIGraphX
-
-MIGraphX uses MIOpen kernels to target AMD GPU. For the model compiled with MIGraphX, tune MIOpen to pick the best possible kernel implementation. The MIOpen tuning results in a significant performance boost. Tuning can be done by setting the environment variable `MIOPEN_FIND_ENFORCE=3`.
-
-:::{note}
-    The tuning process can take a long time to finish.
-:::
-
-**Example:** The average inference time of the inception model example shown previously over 100 iterations using untuned kernels is 0.01383ms. After tuning, it reduces to 0.00459ms, which is a 3x improvement. This result is from ROCm v4.5 on a MI100 GPU.
-
-:::{note}
-    The results may vary depending on the system configurations.
-:::
-
-For reference, the following code snippet shows inference runs for only the first 10 iterations for both tuned and untuned kernels:
-
-```console
-### UNTUNED ###
-iterator : 0
-Inference complete
-Inference time: 0.063ms
-iterator : 1
-Inference complete
-Inference time: 0.008ms
-iterator : 2
-Inference complete
-Inference time: 0.007ms
-iterator : 3
-Inference complete
-Inference time: 0.007ms
-iterator : 4
-Inference complete
-Inference time: 0.007ms
-iterator : 5
-Inference complete
-Inference time: 0.008ms
-iterator : 6
-Inference complete
-Inference time: 0.007ms
-iterator : 7
-Inference complete
-Inference time: 0.028ms
-iterator : 8
-Inference complete
-Inference time: 0.029ms
-iterator : 9
-Inference complete
-Inference time: 0.029ms
-
-### TUNED ###
-iterator : 0
-Inference complete
-Inference time: 0.063ms
-iterator : 1
-Inference complete
-Inference time: 0.004ms
-iterator : 2
-Inference complete
-Inference time: 0.004ms
-iterator : 3
-Inference complete
-Inference time: 0.004ms
-iterator : 4
-Inference complete
-Inference time: 0.004ms
-iterator : 5
-Inference complete
-Inference time: 0.004ms
-iterator : 6
-Inference complete
-Inference time: 0.004ms
-iterator : 7
-Inference complete
-Inference time: 0.004ms
-iterator : 8
-Inference complete
-Inference time: 0.004ms
-iterator : 9
-Inference complete
-Inference time: 0.004ms
-```
-
-### YModel
-
-The best inference performance through MIGraphX is conditioned upon having tuned kernel configurations stored in a `/home` local User Database (DB). If a user were to move their model to a different server or allow a different user to use it, they would have to run through the MIOpen tuning process again to populate the next User DB with the best kernel configurations and corresponding solvers.
-
-Tuning is time consuming, and if the users have not performed tuning, they would see discrepancies between expected or claimed inference performance and actual inference performance. This has led to repetitive and time-consuming tuning tasks for each user.
-
-MIGraphX introduces a feature, known as YModel, that stores the kernel config parameters found during tuning into a `.mxr` file. This ensures the same level of expected performance, even when a model is copied to a different user/system.
-
-The YModel feature is available starting from ROCm 5.4.1 and UIF 1.1.
-
-#### YModel example
-
-Through the `migraphx-driver` functionality, you can generate `.mxr` files with tuning information stored inside it by passing additional `--binary --output model.mxr` to `migraphx-driver` along with the rest of the necessary flags.
-
-For example, to generate `.mxr` file from the ONNX model, use the following:
-
-```bash
-./path/to/migraphx-driver compile --onnx resnet50.onnx --enable-offload-copy --binary --output resnet50.mxr
-```
-
-To run generated `.mxr` files through `migraphx-driver`, use the following:
-
-```bash
-./path/to/migraphx-driver run --migraphx resnet50.mxr --enable-offload-copy
-```
-
-Alternatively, you can use the MIGraphX C++ or Python API to generate `.mxr` files.
-
-![Generating an MXR file](../data/conceptual/image018.png "Generating an MXR file")

docs/conceptual/oversubscription.rst

@@ -0,0 +1,34 @@
+.. meta::
+   :description: Learn what causes oversubscription.
+   :keywords: warning, log, gpu, performance penalty, help
+
+*******************************************************************
+Oversubscription of hardware resources in AMD Instinct accelerators
+*******************************************************************
+
+When an AMD Instinct™ MI series accelerator enters an oversubscribed state, the ``amdgpu`` driver outputs the following
+message.
+
+``amdgpu: Runlist is getting oversubscribed. Expect reduced ROCm performance.``
+
+Oversubscription occurs when application demands exceed the available hardware resources. In an oversubscribed
+state, the hardware scheduler tries to manage resource usage in a round-robin fashion. However,
+this can result in reduced performance, as resources might be occupied by applications or queues not actively
+submitting work. The granularity of hardware resources occupied by an inactive queue can be in the order of
+milliseconds, during which the accelerator or GPU is effectively blocked and unable to process work submitted by other
+queues.
+
+What triggers oversubscription?
+===============================
+
+The system enters an oversubscribed state when one of the following conditions is met:
+
+* **Hardware queue limit exceeded**: The number of user-mode compute queues requested by applications exceeds the
+  hardware limit of 24 queues for current Instinct accelerators.
+
+* **Virtual memory context slots exceeded**: The number of user processes exceeds the number of available virtual memory
+  context slots, which is 11 for current Instinct accelerators.
+
+* **Multiple processes using cooperative workgroups**: More than one process attempts to use the cooperative workgroup
+  feature, leading to resource contention.
+

docs/conf.py

@@ -81,6 +81,7 @@ article_pages = [
         "file": "how-to/llm-fine-tuning-optimization/profiling-and-debugging",
         "os": ["linux"],
     },
+    {"file": "how-to/performance-validation/mi300x/vllm-benchmark", "os": ["linux"]},
     {"file": "how-to/system-optimization/index", "os": ["linux"]},
     {"file": "how-to/system-optimization/mi300x", "os": ["linux"]},
     {"file": "how-to/system-optimization/mi200", "os": ["linux"]},

docs/contribute/building.md

@@ -7,17 +7,14 @@
 
 # Building documentation
 
-You can build our documentation via GitHub (in a pull request) or locally (using the command line or
-Visual Studio (VS) Code.
-
 ## GitHub
 
-If you open a pull request on the `develop` branch of a ROCm repository and scroll to the bottom of
-the page, there is a summary panel. Next to the line
-`docs/readthedocs.com:advanced-micro-devices-demo`, there is a `Details` link. If you click this, it takes
-you to the Read the Docs build for your pull request.
+If you open a pull request and scroll down to the summary panel,
+there is a commit status section. Next to the line
+`docs/readthedocs.com:advanced-micro-devices-demo`, there is a `Details` link.
+If you click this, it takes you to the Read the Docs build for your pull request.
 
-![Screenshot of the GitHub documentation build link](../data/contribute/github-docs-build.png)
+![GitHub PR commit status](../data/contribute/commit-status.png)
 
 If you don't see this line, click `Show all checks` to get an itemized view.
 

docs/contribute/contributing.md

@@ -4,113 +4,68 @@
   <meta name="keywords" content="ROCm, contributing, contribute, maintainer, contributor">
 </head>
 
-# Contribute to ROCm documentation
+# Contributing to the ROCm documentation
 
-All ROCm projects are GitHub-based, so if you want to contribute, you can do so by:
+The ROCm documentation, like all of ROCm, is open source and available on GitHub. You can contribute to the ROCm documentation by forking the appropriate repository, making your changes, and opening a pull request.
 
-* [Submitting a pull request in the appropriate GitHub repository](#submit-a-pull-request)
-* [Creating an issue in the appropriate GitHub repository](#create-an-issue)
-* [Suggesting a new feature](#suggest-a-new-feature)
+To provide feedback on the ROCm documentation, including submitting an issue or suggesting a feature, see [Providing feedback about the ROCm documentation](./feedback.md).
 
-```{important}
-By creating a pull request (PR), you agree to allow your contribution to be licensed under the terms of the
-LICENSE.txt file in the corresponding repository. Different repositories may use different licenses.
-```
+## The ROCm repositories
 
-## Submit a pull request
+The repositories for ROCm and all ROCm components are available on GitHub.
 
-To make edits to our documentation via PR, follow these steps:
+| Module | Documentation location |
+| --- | --- |
+| ROCm framework | [https://github.com/ROCm/ROCm/tree/develop/docs](https://github.com/ROCm/ROCm/tree/develop/docs) |
+| ROCm installation for Linux | [https://github.com/ROCm/rocm-install-on-linux/tree/develop/docs](https://github.com/ROCm/rocm-install-on-linux/tree/develop/docs) |
+| ROCm HIP SDK installation for Windows |  [https://github.com/ROCm/rocm-install-on-windows/tree/develop/docs](https://github.com/ROCm/rocm-install-on-windows/tree/develop/docs) |
 
-1. Identify the repository and the file you want to update. For example, to update this page, you would
-  need to modify content located in this file:
-  `https://github.com/ROCm/ROCm/blob/develop/docs/contribute/contributing.md`
+Individual components have their own repositories with their own documentation in their own `docs` folders.
 
-2. (optional, but recommended) Fork the repository.
+The sub-folders within the `docs` folders across ROCm are typically structured as follows:
 
-3. Clone the repository locally and (optionally) add your fork. Select the green 'Code' button and copy
-   the URL (e.g., `git@github.com:ROCm/ROCm.git`).
+| Sub-folder name | Documentation type |
+|-------|----------|
+| `install` | Installation instructions, build instructions, and prerequisites |
+| `conceptual` | Important concepts |
+| `how-to` | How to implement specific use cases |
+| `tutorials` | Tutorials |
+| `reference` | API references and other reference resources |
 
-   * From your terminal, run:
+## Editing and adding to the documentation
 
-      ```bash
-      git clone git@github.com:ROCm/ROCm.git
-      ```
+The ROCm documentation is written in [reStructuredText (rst)](https://www.sphinx-doc.org/en/master/usage/restructuredtext/index.html) and [Github-flavoured Markdown](https://github.github.com/gfm/), and follows the [Google developer documentation style guide](https://developers.google.com/style/highlights). reStructuredText is preferred when adding content to the documentation.
 
-   * Optionally add your fork to this local copy of the repository by running:
+To edit or add to the documentation:
 
-      ```bash
-      git add remote <name-of-my-fork> <git@github.com:my-username/ROCm.git>
-      ```
+1. Fork the repository you want to add to or edit.
+2. Clone your fork locally.
+3. Create a new local branch cut from the `develop` branch of the repository.
+4. Make your changes to the documentation.
 
-      To get the URL of your fork, go to your GitHub profile, select the fork and click the green 'Code'
-      button (the same process you followed to get the main GitHub repository URL).
-
-4. Change directory into your local copy of the repository, and run ``git pull`` (or ``git pull origin develop``) to ensure your local copy has the most recent content.
-
-5. Create and checkout a new branch using the following command:
+5. Optionally, build the documentation locally before creating a pull request by running the following commands from within the `docs` folder:
 
     ```bash
-    git checkout -b <branch_name>
-    ```
-
-6. Change directory into the `./docs` folder and make any documentation changes locally using your preferred code editor. Follow the guidelines listed on the
-   [documentation structure](./doc-structure.md) page.
-
-   ```{note}
-   Spell checking is performed for pull requests by {doc}`ROCm Docs Core<rocm-docs-core:index>`. To ensure your PR passes spell checking you might need at add new words or acronyms to the `.wordlist.txt` file as described in {doc}`Spell Check<rocm-docs-core:user_guide/spellcheck>`. 
-   ```
-
-7. Optionally run a local test build of the documentation to ensure the content builds and looks as expected. In your terminal, run the following commands from within the `./docs` folder of your cloned repository:
-
-     ```bash
      pip3 install -r sphinx/requirements.txt  # You only need to run this command once
      python3 -m sphinx -T -E -b html -d _build/doctrees -D language=en . _build/html
      ```
 
-    The build output files are located in the `docs/_build` folder. To preview your build, open the index file
-    (`docs/_build/html/index.html`) file. For more information, see [Building documentation](building.md). To learn
-    more about our build tools, see [Documentation toolchain](toolchain.md).
+    The output files will be located in the `docs/_build` folder. Open `docs/_build/html/index.html` to view the documentation.
 
-8. Commit your changes and push them to GitHub by running:
+    For more information on ROCm build tools, see [Documentation toolchain](toolchain.md).
+6. Push your changes. A GitHub link will be returned in the output of the `git push` command. Open this link in a browser to create the pull request.
 
-    ```bash
-    git add <path-to-my-modified-file> # To add all modified files, you can use: git add .
-    git commit -m "my-updates"
-    git push <name-of-my-fork>
-    ```
+    The documentation is built as part of the checks on pull request, along with spell checking and linting. Scroll to the bottom of your pull request to view all the checks.
 
-    After pushing, you will get a GitHub link in the terminal output. Copy this link and paste it into a
-    browser to create your PR.
+    Verify that the linking and spell checking have passed, and that the documentation was built successfully. New words or acronyms can be added to the [wordlist file](https://github.com/ROCm/rocm-docs-core/blob/develop/.wordlist.txt) as needed.
 
-## Create an issue
+    The Read The Docs build of your pull request can be accessed by clicking on the Details link next to the Read The Docs build check. Verify that your changes are in the build and look as expected.
 
-1. To create a new GitHub issue, select the 'Issues' tab in the appropriate repository
-  (e.g., https://github.com/ROCm/ROCm/issues).
-2. Use the search bar to make sure the issue doesn't already exist.
-3. If your issue is not already listed, select the green 'New issue' button to the right of the page. Select
-  the type of issue and fill in the resulting template.
+    Your pull request will be reviewed by a member of the ROCm documentation team.
 
-### General issue guidelines
+See the [GitHub documentation](https://docs.github.com/en) for information on how to fork and clone a repository, and how to create and push a local branch.
 
-* Use your best judgement for issue creation. If your issue is already listed, upvote the issue and
-  comment or post to provide additional details, such as how you reproduced this issue.
-* If you're not sure if your issue is the same, err on the side of caution and file your issue.
-  You can add a comment to include the issue number (and link) for the similar issue. If we evaluate
-  your issue as being the same as the existing issue, we'll close the duplicate.
-* If your issue doesn't exist, use the issue template to file a new issue.
-  * When filing an issue, be sure to provide as much information as possible, including script output so
-    we can collect information about your configuration. This helps reduce the time required to
-    reproduce your issue.
-  * Check your issue regularly, as we may require additional information to successfully reproduce the
-    issue.
-
-## Suggest a new feature
-
-Use the [GitHub Discussion forum](https://github.com/ROCm/ROCm/discussions)
-(Ideas category) to propose new features. Our maintainers are happy to provide direction and
-feedback on feature development.
-
-## Future development workflow
-
-The current ROCm development workflow is GitHub-based. If, in the future, we change this platform,
-the tools and links may change. In this instance, we will update contribution guidelines accordingly.
+```{important}
+By creating a pull request (PR), you agree to allow your contribution to be licensed under the terms of the
+LICENSE.txt file in the corresponding repository. Different repositories can use different licenses.
+```

docs/contribute/doc-structure.md

@@ -1,219 +0,0 @@
-# Documentation structure
-
-Our documentation follows the Pitchfork folder structure. Most documentation files are stored in the
-`/docs` folder. Some special files (such as release, contributing, and changelog) are stored in the root
-(`/`) folder.
-
-All images are stored in the `/docs/data` folder. An image's file path mirrors that of the documentation
-file where it is used.
-
-Our naming structure uses kebab case; for example, `my-file-name.rst`.
-
-## Supported formats and syntax
-
-Our documentation includes both Markdown and RST files. We are gradually transitioning existing
-Markdown to RST in order to more effectively meet our documentation needs. When contributing,
-RST is preferred; if you must use Markdown, use GitHub-flavored Markdown.
-
-We use [Sphinx Design](https://sphinx-design.readthedocs.io/en/latest/index.html) syntax and compile
-our API references using [Doxygen](https://www.doxygen.nl/).
-
-The following table shows some common documentation components and the syntax convention we
-use for each:
-
-<table>
-<tr>
-<th>Component</th>
-<th>RST syntax</th>
-</tr>
-<tr>
-<td>Code blocks</td>
-<td>
-
-```rst
-
-.. code-block:: language-name
-
-  My code block.
-
-
-```
-
-</td>
-</tr>
-<tr>
-<td>Cross-referencing internal files</td>
-<td>
-
-```rst
-
-:doc:`Title <../path/to/file/filename>`
-
-```
-
-</td>
-</tr>
-<tr>
-<td>External links</td>
-<td>
-
-```rst
-
-`link name  <URL>`_
-
-```
-
-</td>
-</tr>
-<tr>
-<tr>
-<td>Headings</td>
-<td>
-
-```rst
-
-******************
-Chapter title (H1)
-******************
-
-Section title (H2)
-===============
-
-Subsection title (H3)
----------------------
-
-Sub-subsection title (H4)
-^^^^^^^^^^^^^^^^^^^^
-
-
-```
-
-</td>
-</tr>
-<tr>
-<td>Images</td>
-<td>
-
-```rst
-
-.. image:: image1.png
-
-```
-
-</td>
-</tr>
-<tr>
-<td>Internal links</td>
-<td>
-
-```rst
-
-1. Add a tag to the section you want to reference:
-
-.. _my-section-tag: section-1
-
-Section 1
-==========
-
-2. Link to your tag:
-
-As shown in :ref:`section-1`.
-
-```
-
-</td>
-</tr>
-<tr>
-<tr>
-<td>Lists</td>
-<td>
-
-```rst
-
-# Ordered (numbered) list item
-
-* Unordered (bulleted) list item
-
-```
-
-</td>
-</tr>
-<tr>
-<tr>
-<td>Math (block)</td>
-<td>
-
-```rst
-
-.. math::
-
-  A = \begin{pmatrix}
-          0.0 & 1.0 & 1.0 & 3.0 \\
-          4.0 & 5.0 & 6.0 & 7.0 \\
-        \end{pmatrix}
-
-```
-
-</td>
-</tr>
-<tr>
-<td>Math (inline)</td>
-<td>
-
-```rst
-
-:math:`2 \times 2 `
-
-```
-
-</td>
-</tr>
-<tr>
-<td>Notes</td>
-<td>
-
-```rst
-
-.. note::
-
-  My note here.
-
-```
-
-</td>
-</tr>
-<tr>
-<td>Tables</td>
-<td>
-
-```rst
-
-.. csv-table::  Optional title here
-  :widths: 30, 70  #optional column widths
-  :header: "entry1 header", "entry2 header"
-
-   "entry1", "entry2"
-
-```
-
-</td>
-</tr>
-</table>
-
-## Language and style
-
-We use the
-[Google developer documentation style guide](https://developers.google.com/style/highlights) to
-guide our content.
-
-Font size and type, page layout, white space control, and other formatting
-details are controlled via
-[rocm-docs-core](https://github.com/ROCm/rocm-docs-core). If you want to notify us
-of any formatting issues, create a pull request in our
-[rocm-docs-core](https://github.com/ROCm/rocm-docs-core) GitHub repository.
-
-## Building our documentation
-
-<!--  % TODO: Fix the link to be able to work at every files  -->
-To learn how to build our documentation, refer to
-[Building documentation](./building.md).

docs/contribute/feedback.md

@@ -4,12 +4,24 @@
   <meta name="keywords" content="documentation, pull request, GitHub, AMD, ROCm">
 </head>
 
-# Providing feedback
+# Providing feedback about the ROCm documentation
 
-Your feedback is welcome. You can provide feedback either through GitHub Discussions or GitHub Issues.
+Feedback about the ROCm documentation is welcome. You can provide feedback about the ROCm documentation either through GitHub Discussions or GitHub Issues.
 
-Use [GitHub Discussions](https://github.com/ROCm/ROCm/discussions) to ask questions, view announcements, and communicate with other members of the community.
+## Participating in discussions through GitHub Discussions
 
-Use [GitHub Issues](https://github.com/ROCm/ROCm/issues) to submit issues you find with ROCm or with the ROCm documentation.
+You can ask questions, view announcements, suggest new features, and communicate with other members of the community through [GitHub Discussions](https://github.com/ROCm/ROCm/discussions).
 
-For information about contributing to the ROCm repository and creating a pull request (PR), see [Contributing](./contributing.md).
+## Submitting issues through GitHub Issues
+
+You can submit issues through [GitHub Issues](https://github.com/ROCm/ROCm/issues).
+
+When creating a new issue, follow the following guidelines:
+
+1. Always do a search to see if the same issue already exists. If the issue already exists, upvote it, and comment or post to provide any additional details you might have.
+2. If you find an issue that is similar to your issue, log your issue, then add a comment that includes a link to the similar issue, as well as its issue number.
+3. Always provide as much information as possible. This helps reduce the time required to reproduce the issue.
+
+After creating your issue, make sure to check it regularly for any requests for additional information.
+
+For information about contributing content to the ROCm documentation, see [Contributing to the ROCm documentation](./contributing.md).

docs/contribute/toolchain.md

@@ -6,60 +6,47 @@
 
 # ROCm documentation toolchain
 
-Our documentation relies on several open source toolchains and sites.
+The ROCm documentation relies on several open source toolchains and sites.
 
-## `rocm-docs-core`
+## rocm-docs-core
 
 [rocm-docs-core](https://github.com/ROCm/rocm-docs-core) is an AMD-maintained
-project that applies customization for our documentation. This project is the tool most ROCm
-repositories use as part of the documentation build. It is also available as a
-[pip package on PyPI](https://pypi.org/project/rocm-docs-core/).
+project that applies customizations for the ROCm documentation. This project is the tool most ROCm repositories use as part of their documentation build pipeline. It is available as a [pip package on PyPI](https://pypi.org/project/rocm-docs-core/).
 
 See the user and developer guides for rocm-docs-core at
 {doc}`rocm-docs-core documentation<rocm-docs-core:index>`.
 
 ## Sphinx
 
-[Sphinx](https://www.sphinx-doc.org/en/master/) is a documentation generator originally used for
-Python. It is now widely used in the open source community.
+[Sphinx](https://www.sphinx-doc.org/en/master/) is a documentation generator originally used for Python. It is now widely used in the open source community.
 
 ### Sphinx External ToC
 
-[Sphinx External ToC](https://sphinx-external-toc.readthedocs.io/en/latest/intro.html) is a Sphinx
-extension used for ROCm documentation navigation. This tool generates a navigation menu on the left
+[Sphinx External ToC](https://sphinx-external-toc.readthedocs.io/en/latest/intro.html) is a Sphinx extension used for ROCm documentation navigation. This tool generates a navigation menu on the left
 based on a YAML file (`_toc.yml.in`) that contains the table of contents.
 
 ### Sphinx-book-theme
 
-[Sphinx-book-theme](https://sphinx-book-theme.readthedocs.io/en/latest/) is a Sphinx theme that
-defines the base appearance for ROCm documentation. ROCm documentation applies some
-customization, such as a custom header and footer on top of the Sphinx Book Theme.
+[Sphinx-book-theme](https://sphinx-book-theme.readthedocs.io/en/latest/) is a Sphinx theme that defines the base appearance for ROCm documentation. ROCm documentation applies some customization, such as a custom header and footer, on top of the Sphinx Book Theme.
 
 ### Sphinx Design
 
-[Sphinx design](https://sphinx-design.readthedocs.io/en/latest/index.html) is a Sphinx extension that
-adds design functionality. ROCm documentation uses Sphinx Design for grids, cards, and synchronized
-tabs.
+[Sphinx design](https://sphinx-design.readthedocs.io/en/latest/index.html) is a Sphinx extension that adds design functionality. ROCm documentation uses Sphinx Design for grids, cards, and synchronized tabs.
 
 ## Doxygen
 
-[Doxygen](https://www.doxygen.nl/) is a documentation generator that extracts information from inline
-code. ROCm projects typically use Doxygen for public API documentation (unless the upstream project
-uses a different tool).
+[Doxygen](https://www.doxygen.nl/) is a documentation generator that extracts information from in-code comments. It is used for API documentation.
 
 ## Breathe
 
-[Breathe](https://www.breathe-doc.org/) is a Sphinx plugin to integrate Doxygen content.
+[Breathe](https://www.breathe-doc.org/) is a Sphinx plugin for integrating Doxygen content.
 
 ## MyST
 
-[Markedly Structured Text (MyST)](https://myst-tools.org/docs/spec) is an extended flavor of
-Markdown ([CommonMark](https://commonmark.org/)) influenced by reStructuredText (RST) and
-Sphinx. It's integrated into ROCm documentation by the Sphinx extension
-[`myst-parser`](https://myst-parser.readthedocs.io/en/latest/).
-A MyST syntax cheat sheet is available on the [Jupyter reference](https://jupyterbook.org/en/stable/reference/cheatsheet.html) site.
+[Markedly Structured Text (MyST)](https://myst-tools.org/docs/spec) is an extended flavor of Markdown ([CommonMark](https://commonmark.org/)) influenced by reStructuredText (rst) and Sphinx. It is integrated into the ROCm documentation with the [`myst-parser`](https://myst-parser.readthedocs.io/en/latest/) Sphinx extension.
+
+See the [MyST syntax cheat sheet](https://jupyterbook.org/en/stable/reference/cheatsheet.html) at the Jupyter Book site.
 
 ## Read the Docs
 
-[Read the Docs](https://docs.readthedocs.io/en/stable/) is the service that builds and hosts the HTML
-documentation generated using Sphinx to our end users.
+[Read the Docs](https://docs.readthedocs.io/en/stable/) is the service that builds and hosts the HTML version of the ROCm documentation.

docs/how-to/llm-fine-tuning-optimization/llm-inference-frameworks.rst

@@ -16,7 +16,7 @@ This section discusses how to implement `vLLM <https://docs.vllm.ai/en/latest>`_
 vLLM inference
 ==============
 
-vLLM is renowned for its paged attention algorithm that can reduce memory consumption and increase throughput thanks to
+vLLM is renowned for its PagedAttention algorithm that can reduce memory consumption and increase throughput thanks to
 its paging scheme. Instead of allocating GPU high-bandwidth memory (HBM) for the maximum output token lengths of the
 models, the paged attention of vLLM allocates GPU HBM dynamically for its actual decoding lengths. This paged attention
 is also effective when multiple requests share the same key and value contents for a large value of beam search or
@@ -139,9 +139,7 @@ Refer to :ref:`mi300x-vllm-optimization` for performance optimization tips.
 
 ROCm provides a prebuilt optimized Docker image for validating the performance of LLM inference with vLLM 
 on the MI300X accelerator. The Docker image includes ROCm, vLLM, PyTorch, and tuning files in the CSV 
-format. For more information, see the guide to 
-`LLM inference performance validation with vLLM on the AMD Instinct™ MI300X accelerator <https://github.com/ROCm/MAD/blob/develop/benchmark/vllm/README.md>`_ 
-on the ROCm GitHub repository.
+format. For more information, see :doc:`/how-to/performance-validation/mi300x/vllm-benchmark`.
 
 .. _fine-tuning-llms-tgi:
 

docs/how-to/llm-fine-tuning-optimization/model-quantization.rst

@@ -181,7 +181,7 @@ Installing bitsandbytes
       # Clone the github repo
       git clone --recurse https://github.com/ROCm/bitsandbytes.git
       cd bitsandbytes
-      git checkout rocm_enabled
+      git checkout rocm_enabled_multi_backend
 
       # Install dependencies 
       pip install -r requirements-dev.txt

docs/how-to/llm-fine-tuning-optimization/single-gpu-fine-tuning-and-inference.rst

@@ -91,7 +91,7 @@ Setting up the base implementation environment
       # Use -DBNB_ROCM_ARCH to target a specific GPU architecture.
       git clone --recurse https://github.com/ROCm/bitsandbytes.git
       cd bitsandbytes
-      git checkout rocm_enabled
+      git checkout rocm_enabled_multi_backend
       pip install -r requirements-dev.txt
       cmake -DBNB_ROCM_ARCH="gfx942" -DCOMPUTE_BACKEND=hip -S .
       python setup.py install

docs/how-to/performance-validation/mi300x/vllm-benchmark.rst

@@ -0,0 +1,407 @@
+.. meta::
+   :description: Learn how to validate LLM inference performance on MI300X accelerators using AMD MAD and the unified
+                 ROCm Docker image.
+   :keywords: model, MAD, automation, dashboarding, validate
+
+***********************************************************
+LLM inference performance validation on AMD Instinct MI300X
+***********************************************************
+
+.. _vllm-benchmark-unified-docker:
+
+The `ROCm vLLM Docker <https://hub.docker.com/r/rocm/vllm/tags>`_ image offers
+a prebuilt, optimized environment designed for validating large language model
+(LLM) inference performance on the AMD Instinct™ MI300X accelerator. This
+ROCm vLLM Docker image integrates vLLM and PyTorch tailored specifically for the
+MI300X accelerator and includes the following components:
+
+* `ROCm 6.2.1 <https://github.com/ROCm/ROCm>`_
+
+* `vLLM 0.6.4 <https://docs.vllm.ai/en/latest>`_
+
+* `PyTorch 2.5.0 <https://github.com/pytorch/pytorch>`_
+
+* Tuning files (in CSV format)
+
+With this Docker image, you can quickly validate the expected inference
+performance numbers on the MI300X accelerator. This topic also provides tips on
+optimizing performance with popular AI models.
+
+.. hlist::
+   :columns: 6
+
+   * Llama 3.1 8B
+
+   * Llama 3.1 70B
+
+   * Llama 3.1 405B
+
+   * Llama 2 7B
+
+   * Llama 2 70B
+
+   * Mixtral 8x7B
+
+   * Mixtral 8x22B
+
+   * Mixtral 7B
+
+   * Qwen2 7B
+
+   * Qwen2 72B
+
+   * JAIS 13B
+
+   * JAIS 30B
+
+.. _vllm-benchmark-vllm:
+
+.. note::
+
+   vLLM is a toolkit and library for LLM inference and serving. AMD implements
+   high-performance custom kernels and modules in vLLM to enhance performance.
+   See :ref:`fine-tuning-llms-vllm` and :ref:`mi300x-vllm-optimization` for
+   more information.
+
+Getting started
+===============
+
+Use the following procedures to reproduce the benchmark results on an
+MI300X accelerator with the prebuilt vLLM Docker image.
+
+.. _vllm-benchmark-get-started:
+
+1. Disable NUMA auto-balancing.
+
+   To optimize performance, disable automatic NUMA balancing. Otherwise, the GPU
+   might hang until the periodic balancing is finalized. For more information,
+   see :ref:`AMD Instinct MI300X system optimization <mi300x-disable-numa>`.
+
+   .. code-block:: shell
+
+      # disable automatic NUMA balancing
+      sh -c 'echo 0 > /proc/sys/kernel/numa_balancing'
+      # check if NUMA balancing is disabled (returns 0 if disabled)
+      cat /proc/sys/kernel/numa_balancing
+      0
+
+2. Download the :ref:`ROCm vLLM Docker image <vllm-benchmark-unified-docker>`.
+
+   Use the following command to pull the Docker image from Docker Hub.
+
+   .. code-block:: shell
+
+      docker pull rocm/vllm:rocm6.2_mi300_ubuntu20.04_py3.9_vllm_0.6.4
+
+Once setup is complete, you can choose between two options to reproduce the
+benchmark results:
+
+-  :ref:`MAD-integrated benchmarking <vllm-benchmark-mad>`
+
+-  :ref:`Standalone benchmarking <vllm-benchmark-standalone>`
+
+.. _vllm-benchmark-mad:
+
+MAD-integrated benchmarking
+===========================
+
+Clone the ROCm Model Automation and Dashboarding (`<https://github.com/ROCm/MAD>`__) repository to a local
+directory and install the required packages on the host machine.
+
+.. code-block:: shell
+
+   git clone https://github.com/ROCm/MAD
+   cd MAD
+   pip install -r requirements.txt
+
+Use this command to run a performance benchmark test of the Llama 3.1 8B model
+on one GPU with ``float16`` data type in the host machine.
+
+.. code-block:: shell
+
+   export MAD_SECRETS_HFTOKEN="your personal Hugging Face token to access gated models"
+   python3 tools/run_models.py --tags pyt_vllm_llama-3.1-8b --keep-model-dir --live-output --timeout 28800
+
+ROCm MAD launches a Docker container with the name
+``container_ci-pyt_vllm_llama-3.1-8b``. The latency and throughput reports of the
+model are collected in the following path: ``~/MAD/reports_float16/``.
+
+Although the following models are preconfigured to collect latency and
+throughput performance data, you can also change the benchmarking parameters.
+Refer to the :ref:`Standalone benchmarking <vllm-benchmark-standalone>` section.
+
+Available models
+----------------
+
+.. hlist::
+   :columns: 3
+
+   * ``pyt_vllm_llama-3.1-8b``
+
+   * ``pyt_vllm_llama-3.1-70b``
+
+   * ``pyt_vllm_llama-3.1-405b``
+
+   * ``pyt_vllm_llama-2-7b``
+
+   * ``pyt_vllm_llama-2-70b``
+
+   * ``pyt_vllm_mixtral-8x7b``
+
+   * ``pyt_vllm_mixtral-8x22b``
+
+   * ``pyt_vllm_mistral-7b``
+
+   * ``pyt_vllm_qwen2-7b``
+
+   * ``pyt_vllm_qwen2-72b``
+
+   * ``pyt_vllm_jais-13b``
+
+   * ``pyt_vllm_jais-30b``
+
+   * ``pyt_vllm_llama-3.1-8b_fp8``
+
+   * ``pyt_vllm_llama-3.1-70b_fp8``
+
+   * ``pyt_vllm_llama-3.1-405b_fp8``
+
+   * ``pyt_vllm_mixtral-8x7b_fp8``
+
+   * ``pyt_vllm_mixtral-8x22b_fp8``
+
+.. _vllm-benchmark-standalone:
+
+Standalone benchmarking
+=======================
+
+You can run the vLLM benchmark tool independently by starting the
+:ref:`Docker container <vllm-benchmark-get-started>` as shown in the following
+snippet.
+
+.. code-block::
+
+   docker pull rocm/vllm:rocm6.2_mi300_ubuntu20.04_py3.9_vllm_0.6.4
+   docker run -it --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128G --security-opt seccomp=unconfined --security-opt apparmor=unconfined --cap-add=SYS_PTRACE -v $(pwd):/workspace --env HUGGINGFACE_HUB_CACHE=/workspace --name vllm_v0.6.4 rocm/vllm:rocm6.2_mi300_ubuntu20.04_py3.9_vllm_0.6.4
+
+In the Docker container, clone the ROCm MAD repository and navigate to the
+benchmark scripts directory at ``~/MAD/scripts/vllm``.
+
+.. code-block::
+
+   git clone https://github.com/ROCm/MAD
+   cd MAD/scripts/vllm
+
+Command
+-------
+
+To start the benchmark, use the following command with the appropriate options.
+See :ref:`Options <vllm-benchmark-standalone-options>` for the list of
+options and their descriptions.
+
+.. code-block:: shell
+
+   ./vllm_benchmark_report.sh -s $test_option -m $model_repo -g $num_gpu -d $datatype
+
+See the :ref:`examples <vllm-benchmark-run-benchmark>` for more information.
+
+.. note::
+
+   The input sequence length, output sequence length, and tensor parallel (TP) are
+   already configured. You don't need to specify them with this script.
+
+.. note::
+
+   If you encounter the following error, pass your access-authorized Hugging
+   Face token to the gated models.
+
+   .. code-block:: shell
+
+      OSError: You are trying to access a gated repo.
+
+      # pass your HF_TOKEN
+      export HF_TOKEN=$your_personal_hf_token
+
+.. _vllm-benchmark-standalone-options:
+
+Options
+-------
+
+.. list-table::
+   :header-rows: 1
+   :align: center
+
+   * - Name
+     - Options
+     - Description
+
+   * - ``$test_option``
+     - latency
+     - Measure decoding token latency
+
+   * -
+     - throughput
+     - Measure token generation throughput
+
+   * -
+     - all
+     - Measure both throughput and latency
+
+   * - ``$model_repo``
+     - ``meta-llama/Meta-Llama-3.1-8B-Instruct``
+     - Llama 3.1 8B
+
+   * - (``float16``)
+     - ``meta-llama/Meta-Llama-3.1-70B-Instruct``
+     - Llama 3.1 70B
+
+   * -
+     - ``meta-llama/Meta-Llama-3.1-405B-Instruct``
+     - Llama 3.1 405B
+
+   * -
+     - ``meta-llama/Llama-2-7b-chat-hf``
+     - Llama 2 7B
+
+   * -
+     - ``meta-llama/Llama-2-70b-chat-hf``
+     - Llama 2 70B
+
+   * -
+     - ``mistralai/Mixtral-8x7B-Instruct-v0.1``
+     - Mixtral 8x7B
+
+   * -
+     - ``mistralai/Mixtral-8x22B-Instruct-v0.1``
+     - Mixtral 8x22B
+
+   * -
+     - ``mistralai/Mistral-7B-Instruct-v0.3``
+     - Mixtral 7B
+
+   * -
+     - ``Qwen/Qwen2-7B-Instruct``
+     - Qwen2 7B
+
+   * -
+     - ``Qwen/Qwen2-72B-Instruct``
+     - Qwen2 72B
+
+   * -
+     - ``core42/jais-13b-chat``
+     - JAIS 13B
+
+   * -
+     - ``core42/jais-30b-chat-v3``
+     - JAIS 30B
+
+   * - ``$model_repo``
+     - ``amd/Meta-Llama-3.1-8B-Instruct-FP8-KV``
+     - Llama 3.1 8B
+
+   * - (``float8``)
+     - ``amd/Meta-Llama-3.1-70B-Instruct-FP8-KV``
+     - Llama 3.1 70B
+
+   * -
+     - ``amd/Meta-Llama-3.1-405B-Instruct-FP8-KV``
+     - Llama 3.1 405B
+
+   * -
+     - ``amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV``
+     - Mixtral 8x7B
+
+   * -
+     - ``amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV``
+     - Mixtral 8x22B
+
+   * - ``$num_gpu``
+     - 1 or 8
+     - Number of GPUs
+
+   * - ``$datatype``
+     - ``float16`` or ``float8``
+     - Data type
+
+.. _vllm-benchmark-run-benchmark:
+
+Running the benchmark on the MI300X accelerator
+-----------------------------------------------
+
+Here are some examples of running the benchmark with various options.
+See :ref:`Options <vllm-benchmark-standalone-options>` for the list of
+options and their descriptions.
+
+Example 1: latency benchmark
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+ 
+Use this command to benchmark the latency of the Llama 3.1 8B model on one GPU with the ``float16`` and ``float8`` data types.
+
+.. code-block::
+
+   ./vllm_benchmark_report.sh -s latency -m meta-llama/Meta-Llama-3.1-8B-Instruct -g 1 -d float16
+   ./vllm_benchmark_report.sh -s latency -m amd/Meta-Llama-3.1-8B-Instruct-FP8-KV -g 1 -d float8
+
+Find the latency reports at:
+
+- ``./reports_float16/summary/Meta-Llama-3.1-8B-Instruct_latency_report.csv``
+
+- ``./reports_float8/summary/Meta-Llama-3.1-8B-Instruct-FP8-KV_latency_report.csv``
+
+Example 2: throughput benchmark
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Use this command to benchmark the throughput of the Llama 3.1 8B model on one GPU with the ``float16`` and ``float8`` data types.
+
+.. code-block:: shell
+
+   ./vllm_benchmark_report.sh -s throughput -m meta-llama/Meta-Llama-3.1-8B-Instruct -g 1 -d float16
+   ./vllm_benchmark_report.sh -s throughput -m amd/Meta-Llama-3.1-8B-Instruct-FP8-KV -g 1 -d float8
+
+Find the throughput reports at:
+
+- ``./reports_float16/summary/Meta-Llama-3.1-8B-Instruct_throughput_report.csv``
+
+- ``./reports_float8/summary/Meta-Llama-3.1-8B-Instruct-FP8-KV_throughput_report.csv``
+
+.. raw:: html
+
+   <style>
+   mjx-container[jax="CHTML"][display="true"] {
+       text-align: left;
+       margin: 0;
+   }
+   </style>
+
+.. note::
+
+   Throughput is calculated as:
+
+   - .. math:: throughput\_tot = requests \times (\mathsf{\text{input lengths}} + \mathsf{\text{output lengths}}) / elapsed\_time
+
+   - .. math:: throughput\_gen = requests \times \mathsf{\text{output lengths}} / elapsed\_time
+
+Further reading
+===============
+
+- For application performance optimization strategies for HPC and AI workloads,
+  including inference with vLLM, see :doc:`/how-to/tuning-guides/mi300x/workload`.
+
+- To learn more about the options for latency and throughput benchmark scripts,
+  see `<https://github.com/ROCm/vllm/tree/main/benchmarks>`_.
+
+- To learn more about system settings and management practices to configure your system for
+  MI300X accelerators, see :doc:`/how-to/system-optimization/mi300x`.
+
+- To learn how to run LLM models from Hugging Face or your own model, see
+  :doc:`Using ROCm for AI </how-to/rocm-for-ai/index>`.
+
+- To learn how to optimize inference on LLMs, see
+  :doc:`Fine-tuning LLMs and inference optimization </how-to/llm-fine-tuning-optimization/index>`.
+
+- For a list of other ready-made Docker images for ROCm, see the
+  :doc:`Docker image support matrix <rocm-install-on-linux:reference/docker-image-support-matrix>`.
+
+- To compare with the previous version of the ROCm vLLM Docker image for performance validation, refer to
+  `LLM inference performance validation on AMD Instinct MI300X (ROCm 6.2.0) <https://rocm.docs.amd.com/en/docs-6.2.0/how-to/performance-validation/mi300x/vllm-benchmark.html>`_.
+

docs/how-to/rocm-for-ai/deploy-your-model.rst

@@ -46,9 +46,7 @@ Validating vLLM performance
 
 ROCm provides a prebuilt optimized Docker image for validating the performance of LLM inference with vLLM 
 on the MI300X accelerator. The Docker image includes ROCm, vLLM, PyTorch, and tuning files in the CSV 
-format. For more information, see the guide to 
-`LLM inference performance validation with vLLM on the AMD Instinct™ MI300X accelerator <https://github.com/ROCm/MAD/blob/develop/benchmark/vllm/README.md>`_ 
-on the ROCm GitHub repository.
+format. For more information, see :doc:`/how-to/performance-validation/mi300x/vllm-benchmark`.
 
 .. _rocm-for-ai-serve-hugging-face-tgi:
 

docs/how-to/system-optimization/mi100.md

@@ -342,8 +342,8 @@ If SMT is enabled by setting "CCD/Core/Thread Enablement > SMT Control" to
 (logical) cores of the system:
 
 * In the server BIOS, set IOMMU to "Enabled".
-* When configuring the Grub boot loader, add the following arguments for the
-  Linux kernel: `amd_iommu=on iommu=pt`
+* When configuring the Grub boot loader, add the following argument for the
+  Linux kernel: `iommu=pt`
 * Update Grub to use the modified configuration:
 
   ```shell
@@ -355,7 +355,7 @@ If SMT is enabled by setting "CCD/Core/Thread Enablement > SMT Control" to
 
   ```none
   [...]
-  [   0.000000] Kernel command line: [...] amd_iommu=on iommu=pt
+  [   0.000000] Kernel command line: [...] iommu=pt
      [...]
   ```
 

docs/how-to/system-optimization/mi200.md

@@ -327,8 +327,8 @@ If SMT is enabled by setting "CCD/Core/Thread Enablement > SMT Control" to
 (logical) cores of the system:
 
 * In the server BIOS, set IOMMU to "Enabled".
-* When configuring the Grub boot loader, add the following arguments for the
-  Linux kernel: `amd_iommu=on iommu=pt`
+* When configuring the Grub boot loader, add the following argument for the
+  Linux kernel: `iommu=pt`
 * Update Grub to use the modified configuration:
 
   ```shell
@@ -340,7 +340,7 @@ If SMT is enabled by setting "CCD/Core/Thread Enablement > SMT Control" to
 
   ```none
   [...]
-  [   0.000000] Kernel command line: [...] amd_iommu=on iommu=pt
+  [   0.000000] Kernel command line: [...] iommu=pt
      [...]
   ```
 

docs/how-to/system-optimization/mi300x.rst

@@ -299,7 +299,7 @@ For a system that has AMD host CPUs add this to ``GRUB_CMDLINE_LINUX``:
 
 .. code-block:: text
 
-   amd_iommu=on iommu=pt
+   iommu=pt
 
 Otherwise, if the system has Intel host CPUs add this instead to
 ``GRUB_CMDLINE_LINUX``:
@@ -500,7 +500,7 @@ If SMT is enabled by setting ``CCD/Core/Thread Enablement > SMT Control`` to
 
 #. In the server BIOS, set IOMMU to ``Enabled``.
 
-#. When configuring the GRUB boot loader, add the following arguments for the Linux kernel: ``amd_iommu=on iommu=pt``.
+#. When configuring the GRUB boot loader, add the following argument for the Linux kernel: ``iommu=pt``.
 
 #. Update GRUB.
 
@@ -515,7 +515,7 @@ If SMT is enabled by setting ``CCD/Core/Thread Enablement > SMT Control`` to
 .. code-block:: shell
 
    [...]
-   [   0.000000] Kernel command line: [...] amd_iommu=on iommu=pt
+   [   0.000000] Kernel command line: [...] iommu=pt
    [...]
 
 Once the system is properly configured, ROCm software can be

docs/how-to/system-optimization/w6000-v620.md

@@ -111,7 +111,7 @@ sudo virsh net-start default /*to enable Virtual network by default
 Enable input-output memory management unit (IOMMU) in GRUB settings by adding the following line to `/etc/default/grub`:
 
 ```none
-GRUB_CMDLINE_LINUX_DEFAULT="quiet splash amd_iommu=on" for AMD CPU
+GRUB_CMDLINE_LINUX_DEFAULT="quiet splash" for AMD CPU
 ```
 
 Update grub and reboot

docs/how-to/tuning-guides/mi300x/index.rst

@@ -8,6 +8,8 @@ accelerators. They include detailed instructions on system settings and
 application tuning suggestions to help you fully leverage the capabilities of
 these accelerators, thereby achieving optimal performance.
 
+* :doc:`/how-to/performance-validation/mi300x/vllm-benchmark`
+
 * :doc:`/how-to/tuning-guides/mi300x/system`
 
 * :doc:`/how-to/tuning-guides/mi300x/workload`

docs/how-to/tuning-guides/mi300x/workload.rst

@@ -152,9 +152,7 @@ address any new bottlenecks that may emerge.
 
 ROCm provides a prebuilt optimized Docker image that has everything required to implement
 the tips in this section. It includes ROCm, vLLM, PyTorch, and tuning files in the CSV 
-format. For more information, see the guide to 
-`LLM inference performance validation with vLLM on the AMD Instinct™ MI300X accelerator <https://github.com/ROCm/MAD/blob/develop/benchmark/vllm/README.md>`_ 
-on the ROCm GitHub repository.
+format. For more information, see :doc:`/how-to/performance-validation/mi300x/vllm-benchmark`.
 
 .. _mi300x-profiling-tools:
 
@@ -378,11 +376,10 @@ Refer to `vLLM documentation <https://docs.vllm.ai/en/latest/models/performance.
 for additional performance tips. :ref:`fine-tuning-llms-vllm` describes vLLM
 usage with ROCm.
 
-ROCm provides a prebuilt optimized Docker image for validating the performance of LLM inference with vLLM 
-on the MI300X accelerator. The Docker image includes ROCm, vLLM, PyTorch, and tuning files in the CSV 
-format. For more information, see the guide to 
-`LLM inference performance validation with vLLM on the AMD Instinct™ MI300X accelerator <https://github.com/ROCm/MAD/blob/develop/benchmark/vllm/README.md>`_ 
-on the ROCm GitHub repository.
+ROCm provides a prebuilt optimized Docker image for validating the performance
+of LLM inference with vLLM on the MI300X accelerator. The Docker image includes
+ROCm, vLLM, PyTorch, and tuning files in the CSV format. For more information,
+see :doc:`/how-to/performance-validation/mi300x/vllm-benchmark`.
 
 Maximize throughput
 -------------------

docs/index.md

@@ -11,7 +11,7 @@ ROCm is an open-source software platform optimized to extract HPC and AI workloa
 performance from AMD Instinct accelerators and AMD Radeon GPUs while maintaining
 compatibility with industry software frameworks. For more information, see [What is ROCm?](./what-is-rocm.rst)
 
-If you're using Radeon GPUs, consider reviewing {doc}`Radeon-specific ROCm documentation<radeon:index>`.
+If you're using AMD Radeon™ PRO or Radeon GPUs in a workstation setting with a display connected, review {doc}`Radeon-specific ROCm documentation<radeon:index>`.
 
 Installation instructions are available from:
 
@@ -45,7 +45,8 @@ ROCm documentation is organized into the following categories:
 * [Using ROCm for HPC](./how-to/rocm-for-hpc/index.rst)
 * [Fine-tuning LLMs and inference optimization](./how-to/llm-fine-tuning-optimization/index.rst)
 * [System optimization](./how-to/system-optimization/index.rst)
-* [AMD Instinct MI300X tuning guides](./how-to/tuning-guides/mi300x/index.rst)
+* [AMD Instinct MI300X performance validation and tuning](./how-to/tuning-guides/mi300x/index.rst)
+* [GPU cluster networking](https://dcgpu.docs.amd.com/projects/gpu-cluster-networking/en/latest/index.html)
 * [System debugging](./how-to/system-debugging.md)
 * [Using MPI](./how-to/gpu-enabled-mpi.rst)
 * [Using advanced compiler features](./conceptual/compiler-topics.md)
@@ -63,7 +64,7 @@ ROCm documentation is organized into the following categories:
 * [Using CMake](./conceptual/cmake-packages.rst)
 * [ROCm & PCIe atomics](./conceptual/More-about-how-ROCm-uses-PCIe-Atomics.rst)
 * [Inception v3 with PyTorch](./conceptual/ai-pytorch-inception.md)
-* [Inference optimization with MIGraphX](./conceptual/ai-migraphx-optimization.md)
+* [Oversubscription of hardware resources](./conceptual/oversubscription.rst)
 :::
 
 <!-- markdownlint-disable MD051 -->

docs/sphinx/_toc.yml.in

@@ -70,16 +70,18 @@ subtrees:
       - file: how-to/system-optimization/w6000-v620.md
         title: AMD RDNA 2
   - file: how-to/tuning-guides/mi300x/index.rst
-    title: AMD MI300X tuning guides
+    title: AMD MI300X performance validation and tuning
     subtrees:
     - entries:
+      - file: how-to/performance-validation/mi300x/vllm-benchmark.rst
+        title: Performance validation
       - file: how-to/tuning-guides/mi300x/system.rst
         title: System tuning
       - file: how-to/tuning-guides/mi300x/workload.rst
         title: Workload tuning
-  - file: how-to/system-debugging.md
   - file: how-to/gpu-enabled-mpi.rst
     title: Using MPI
+  - file: how-to/system-debugging.md
   - file: conceptual/compiler-topics.md
     title: Using advanced compiler features
     subtrees:
@@ -156,8 +158,8 @@ subtrees:
     title: ROCm & PCIe atomics
   - file: conceptual/ai-pytorch-inception.md
     title: Inception v3 with PyTorch
-  - file: conceptual/ai-migraphx-optimization.md
-    title: Inference optimization with MIGraphX
+  - file: conceptual/oversubscription.rst
+    title: Oversubscription of hardware resources
 
 - caption: Reference
   entries:
@@ -173,16 +175,13 @@ subtrees:
 - caption: Contribute
   entries:
   - file: contribute/contributing.md
-    title: Contribute to ROCm docs
+    title: Contributing to the ROCm docmentation
     subtrees:
     - entries:
-      - file: contribute/doc-structure.md
-        title: Documentation structure
       - file: contribute/toolchain.md
-        title: Documentation toolchain
+        title: ROCm documentation toolchain
       - file: contribute/building.md
-        title: Build our documentation
   - file: contribute/feedback.md
-    title: Provide feedback
+    title: Providing feedback about the ROCm documentation
   - file: about/license.md
-    title: ROCm license
+    title: ROCm licenses

docs/sphinx/requirements.in

@@ -1,2 +1,2 @@
-rocm-docs-core==1.8.1
+rocm-docs-core==1.8.2
 sphinx-reredirects

docs/sphinx/requirements.txt

@@ -92,7 +92,7 @@ requests==2.32.3
     # via
     #   pygithub
     #   sphinx
-rocm-docs-core==1.8.1
+rocm-docs-core==1.8.2
     # via -r requirements.in
 smmap==5.0.1
     # via gitdb

tools/autotag/templates/highlights/5.3.0.md

@@ -184,5 +184,5 @@ clinfo, and HelloWord.cl and cause a system crash.
 * IRQ remapping does not support X2APIC mode
 * NMI error
 
-Workaround: To avoid the system crash, add `amd_iommu=on iommu=pt` as the kernel bootparam, as
+Workaround: To avoid the system crash, add `iommu=pt` as the kernel bootparam, as
 indicated in the warning message.