Apply suggestion from @mattwill-amd

Adding a note for a link to the Optiq docs

CHANGELOG.md

@@ -39,7 +39,11 @@ for a complete overview of this release.
   - VMs were incorrectly reporting `AMDSMI_STATUS_API_FAILED` when unable to get the power cap within the `amdsmi_get_power_info`.
   - The API now returns `N/A` or `UINT_MAX` for values that can't be retrieved, instead of failing.
 
-- Fixed output for `amd-smi xgmi -l --json`.  
+- Fixed output for `amd-smi xgmi -l --json`.
+
+```{note}
+See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md#amd_smi_lib-for-rocm-711) for details, examples, and in-depth descriptions.
+```
 
 ### **Composable Kernel** (1.1.0)
 

RELEASE.md

@@ -674,7 +674,7 @@ For a historical overview of ROCm component updates, see the {doc}`ROCm consolid
 - Fixed output for `amd-smi xgmi -l --json`.  
 
 ```{note}
-See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md#amd_smi_lib-for-rocm-710) for details, examples, and in-depth descriptions.
+See the full [AMD SMI changelog](https://github.com/ROCm/amdsmi/blob/release/rocm-rel-7.1/CHANGELOG.md#amd_smi_lib-for-rocm-711) for details, examples, and in-depth descriptions.
 ```
 
 ### **Composable Kernel** (1.1.0)
@@ -864,22 +864,6 @@ be fixed in a future ROCm release.
 
 Due to partial data corruption of Electrically Erasable Programmable Read-Only Memory (EEPROM) and limited error handling in the AMD GPU Driver(amdgpu), excessive log output might result when querying the reliability, availability, and serviceability (RAS) bad pages. This issue will be fixed in a future AMD GPU Driver(amdgpu) and ROCm release.
 
-### OpenBLAS runtime dependency for hipblastlt-test and hipblaslt-bench
-
-Running `hipblaslt-test` or `hipblaslt-bench` without installing the OpenBLAS development package results in the following error:
-```
-libopenblas.so.0: cannot open shared object file: No such file or directory
-```
-As a workaround, first install `libopenblas-dev` or `libopenblas-deve`, depending on the package manager used. The issue will be fixed in a future ROCm release. See [GitHub issue #5639](https://github.com/ROCm/ROCm/issues/5639).
-
-### Reduced precision in gemm_ex operations for rocBLAS and hipBLAS
-
-Some `gemm_ex` operations with `half` or `f32_r` data types might yield 16-bit precision results instead of the expected 32-bit precision when matrix dimensions are m=1 or n=1. The issue results from the optimization that enables `_ex` APIs to use lower precision multiples. It limits the high-precision matrix operations performed in PyTorch with rocBLAS and hipBLAS. The issue will be fixed in a future ROCm release. See [GitHub issue #5640](https://github.com/ROCm/ROCm/issues/5640).
-
-### RCCL profiler plugin failure with AllToAll operations
-
-The RCCL profiler plugin `librccl-profiler.so` might fail with a segmentation fault during `AllToAll` collective operations due to improperly assigned point-to-point task function pointers. This leads to invalid memory access and prevents profiling of `AllToAll` performance. Other operations, like `AllReduce`, are unaffected. It's recommended to avoid using the RCCL profiler plugin with `AllToAll` operations until the fix is available. This issue is resolved in the {fab}`github`[RCCL `develop` branch](https://github.com/ROCm/rccl/tree/develop) and will be part of a future ROCm release. See [GitHub issue #5653](https://github.com/ROCm/ROCm/issues/5653).
-
 ## ROCm resolved issues
 
 The following are previously known issues resolved in this release. For resolved issues related to

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

@@ -30,7 +30,7 @@ ROCm Version,7.1.1,7.1.0,7.0.2,7.0.1/7.0.0,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6
       ,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908,gfx908
       ,,,,,,,,,,,,,,,,,,,,,,
       FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
-      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.9, 2.8, 2.7","2.8, 2.7, 2.6","2.8, 2.7, 2.6","2.7, 2.6, 2.5","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13"
+      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.9, 2.8","2.8, 2.7, 2.6","2.8, 2.7, 2.6","2.7, 2.6, 2.5","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.6, 2.5, 2.4, 2.3","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 1.13","2.4, 2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.3, 2.2, 2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13","2.1, 2.0, 1.13"
       :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.20.0, 2.19.1, 2.18.1","2.20.0, 2.19.1, 2.18.1","2.19.1, 2.18.1, 2.17.1 [#tf-mi350-past-60]_","2.19.1, 2.18.1, 2.17.1 [#tf-mi350-past-60]_","2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.18.1, 2.17.1, 2.16.2","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.17.0, 2.16.2, 2.15.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.16.1, 2.15.1, 2.14.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.15.0, 2.14.0, 2.13.1","2.14.0, 2.13.1, 2.12.1","2.14.0, 2.13.1, 2.12.1"
       :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.7.1,0.7.1,0.6.0,0.6.0,0.4.35,0.4.35,0.4.35,0.4.35,0.4.31,0.4.31,0.4.31,0.4.31,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
       :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.3.0.post0,N/A,N/A,N/A,N/A,N/A,N/A

docs/compatibility/compatibility-matrix.rst

@@ -54,7 +54,7 @@ compatibility and system requirements.
       ,gfx908,gfx908,gfx908
       ,,,
       FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix:,,
-      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.9, 2.8, 2.7","2.8, 2.7, 2.6","2.6, 2.5, 2.4, 2.3"
+      :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.9, 2.8","2.8, 2.7, 2.6","2.6, 2.5, 2.4, 2.3"
       :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.20.0, 2.19.1, 2.18.1","2.20.0, 2.19.1, 2.18.1","2.18.1, 2.17.1, 2.16.2"
       :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`,0.7.1,0.7.1,0.4.35
       :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat]_,N/A,N/A,2.4.0

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

@@ -401,25 +401,25 @@ with ROCm.
 
 Key features and enhancements for PyTorch 2.9 with ROCm 7.1.1
 ================================================================================
-- Scaled Dot Product Attention (SDPA) upgraded to use AOTriton version 0.11b
+- Scaled Dot Product Attention (SDPA) upgraded to use AOTriton version 0.11b.
 
-- Default hipBLASLt support enabled for gfx908 architecture on ROCm 6.3 and later
+- Default hipBLASLt support enabled for gfx908 architecture on ROCm 6.3 and later.
 
-- MIOpen now supports channels last memory format for 3D convolutions and batch normalization
+- MIOpen now supports channels last memory format for 3D convolutions and batch normalization.
 
-- NHWC convolution operations in MIOpen optimized by eliminating unnecessary transpose operations
+- NHWC convolution operations in MIOpen optimized by eliminating unnecessary transpose operations.
 
-- Improved tensor.item() performance by removing redundant synchronization
+- Improved tensor.item() performance by removing redundant synchronization.
 
-- Enhanced performance for element-wise operations and reduction kernels
+- Enhanced performance for element-wise operations and reduction kernels.
 
-- Added support for grouped GEMM operations through fbgemm_gpu generative AI components
+- Added support for grouped GEMM operations through fbgemm_gpu generative AI components.
 
-- Resolved device error in Inductor when using CUDA graph trees with HIP
+- Resolved device error in Inductor when using CUDA graph trees with HIP.
 
-- Corrected logsumexp scaling in AOTriton-based SDPA implementation
+- Corrected logsumexp scaling in AOTriton-based SDPA implementation.
 
-- Added stream graph capture status validation in memory copy synchronization functions
+- Added stream graph capture status validation in memory copy synchronization functions.
 
 Key features and enhancements for PyTorch 2.8 with ROCm 7.1
 ================================================================================

docs/what-is-rocm.rst

@@ -123,8 +123,8 @@ Performance
 
 .. note::
 
-  `ROCprof Compute Viewer <https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/amd-mainline/>`_ is a tool for visualizing and analyzing GPU thread trace data collected using :doc:`rocprofv3 <rocprofiler-sdk:index>`.
-  Note that `ROCprof Compute Viewer <https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/amd-mainline/>`_ is in an early access state. Running production workloads is not recommended.
+  - `ROCprof Compute Viewer <https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/amd-mainline/>`_ is a tool for visualizing and analyzing GPU thread trace data collected using :doc:`rocprofv3 <rocprofiler-sdk:index>`. Note that `ROCprof Compute Viewer <https://rocm.docs.amd.com/projects/rocprof-compute-viewer/en/amd-mainline/>`_ is in an early access state. Running production workloads is not recommended.
+  - ROCm Optiq (Beta) provides deep insights into system-level performance for applications running on the ROCm stack. It serves as the GUI to visualize traces collected by ROCm profiling tools, specifically `ROCm Systems Profiler <https://rocm.docs.amd.com/projects/rocprofiler-systems/en/latest/index.html>`_.
 
 Development
 ^^^^^^^^^^^