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700 update pre GA batch1 (#5322)

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* Fix PLDM note for ROCm 7.0 (#5320)

* fix pdlm for mi300x

* update debian 12 support note

* 7.0.0 Release notes update Batch 9 (#559)

* Changelog synced

* Compatibilty updated

* Compatibilty update

* Compiler highlight updated

* wordlist updated

---------

Co-authored-by: Peter Park <peter.park@amd.com>
This commit is contained in:
Pratik Basyal
2025-09-16 07:24:54 -04:00
committed by GitHub
parent 0475650f00
commit 8af34e2026
4 changed files with 27 additions and 22 deletions
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3
.wordlist.txt
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@@ -872,6 +872,8 @@ req
resampling
rescaling
reusability
rhel
rl
RLHF
roadmap
roc
@@ -925,6 +927,7 @@ sglang
shader
sharding
sigmoid
sles
sm
smi
softmax

12
CHANGELOG.md
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@@ -445,7 +445,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Changed
* The NVIDIA backend now requires CUB, Thrust, and libcu++ 2.7.0. If they aren't found, they will be downloaded from the NVIDIA CCCL repository.
* The CUDA backend now requires CUB, Thrust, and libcu++ 2.7.0. If they aren't found, they will be downloaded from the CUDA CCCL repository.
* Updated `thread_load` and `thread_store` to align hipCUB with CUB.
* All kernels now have hidden symbol visibility. All symbols now have inline namespaces that include the library version, (for example, `hipcub::HIPCUB_300400_NS::symbol` instead of `hipcub::symbol`), letting the user link multiple libraries built with different versions of hipCUB.
* Modified the broadcast kernel in warp scan benchmarks. The reported performance may be different to previous versions.
@@ -469,7 +469,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Known issues
* `BlockAdjacentDifference::FlagHeads`, `BlockAdjacentDifference::FlagTails` and `BlockAdjacentDifference::FlagHeadsAndTails` have been removed from hipCUB's CUB backend. They were already deprecated as of version 2.12.0 of hipCUB and they were removed from CCCL (CUB) as of CCCL's 2.6.0 release.
* `BlockScan::InclusiveScan` for the NVIDIA backend does not compute the block aggregate correctly when passing an initial value parameter. This behavior is not matched by the AMD backend.
* `BlockScan::InclusiveScan` for the CUDA backend does not compute the block aggregate correctly when passing an initial value parameter. This behavior is not matched by the AMD backend.
#### Upcoming changes
@@ -491,7 +491,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Added
* Documentation clarifying how hipfort is built for the NVIDIA platform.
* Documentation clarifying how hipfort is built for the CUDA platform.
#### Changed
@@ -538,7 +538,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Resolved issues
* Corrected the value of `lwork` returned by various `bufferSize` functions to be consistent with NVIDIA cuSOLVER. The following functions now return `lwork` so that the workspace size (in bytes) is `sizeof(T) * lwork`, rather than `lwork`. To restore the original behavior, set the environment variable `HIPSOLVER_BUFFERSIZE_RETURN_BYTES`.
* Corrected the value of `lwork` returned by various `bufferSize` functions to be consistent with CUDA cuSOLVER. The following functions now return `lwork` so that the workspace size (in bytes) is `sizeof(T) * lwork`, rather than `lwork`. To restore the original behavior, set the environment variable `HIPSOLVER_BUFFERSIZE_RETURN_BYTES`.
* `hipsolverXorgbr_bufferSize`, `hipsolverXorgqr_bufferSize`, `hipsolverXorgtr_bufferSize`, `hipsolverXormqr_bufferSize`, `hipsolverXormtr_bufferSize`, `hipsolverXgesvd_bufferSize`, `hipsolverXgesvdj_bufferSize`, `hipsolverXgesvdBatched_bufferSize`, `hipsolverXgesvdaStridedBatched_bufferSize`, `hipsolverXsyevd_bufferSize`, `hipsolverXsyevdx_bufferSize`, `hipsolverXsyevj_bufferSize`, `hipsolverXsyevjBatched_bufferSize`, `hipsolverXsygvd_bufferSize`, `hipsolverXsygvdx_bufferSize`, `hipsolverXsygvj_bufferSize`, `hipsolverXsytrd_bufferSize`, `hipsolverXsytrf_bufferSize`.
### **hipSPARSE** (4.0.1)
@@ -566,7 +566,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Known issues
* In `hipsparseSpSM_solve()`, the external buffer is passed as a parameter. This does not match the NVIDIA CUDA cuSPARSE API. This extra external buffer parameter will be removed in a future release. For now, this extra parameter can be ignored and nullptr passed in because it is unused internally.
* In `hipsparseSpSM_solve()`, the external buffer is passed as a parameter. This does not match the CUDA cuSPARSE API. This extra external buffer parameter will be removed in a future release. For now, this extra parameter can be ignored and nullptr passed in because it is unused internally.
### **hipSPARSELt** (0.2.4)
@@ -640,7 +640,7 @@ HIP runtime has the following functional improvements which improves runtime per
* `llvm-flang`, AMD's next-generation Fortran compiler. It's a re-implementation of the Fortran frontend that can be found at `llvm/llvm-project/flang` on GitHub.
* Comgr support for an in-memory virtual file system (VFS) for storing temporary files generated during intermediate compilation steps to improve performance in the device library link step.
* Compiler support of a new target-specific builtin `__builtin_amdgcn_processor_is` for late or deferred queries of the current target processor, and `__builtin_amdgcn_is_invocable` to determine the current target processor ability to invoke a particular builtin.
* HIPIFY support for NVIDIA CUDA 12.9.1 APIs. Added support for all new device and host APIs, including FP4, FP6, and FP128, and support for the corresponding ROCm HIP equivalents.
* HIPIFY support for CUDA 12.9.1 APIs. Added support for all new device and host APIs, including FP4, FP6, and FP128, and support for the corresponding ROCm HIP equivalents.
#### Changed

22
RELEASE.md
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@@ -61,7 +61,7 @@ for more information about operating system and hardware compatibility.
ROCm 7.0.0 introduces support for KVM Passthrough for AMD Instinct MI350X and MI355X GPUs.
All KVM-based SR-IOV supported configurations require the GIM SR-IOV driver version 8.4.0.K. In addition, support for VMware ESXi 8 has been introduced for AMD Instinct MI300X GPUs. For more information, see [Virtualization Support](https://rocm.docs.amd.com/projects/install-on-linux-internal/en/latest/reference/system-requirements.html#virtualization-support).
All KVM-based SR-IOV supported configurations require the GIM SR-IOV driver version 8.4.0.K. Refer to [GIM Release note](https://github.com/amd/MxGPU-Virtualization/releases) for more details. In addition, support for VMware ESXi 8 has been introduced for AMD Instinct MI300X GPUs. For more information, see [Virtualization Support](https://rocm.docs.amd.com/projects/install-on-linux-internal/en/latest/reference/system-requirements.html#virtualization-support).
### Deep learning and AI framework updates
@@ -179,13 +179,11 @@ Key compiler enhancements include:
Each kernel in the linked LTO module can be put in a separate partition, and any non-inlined function it depends on can be copied alongside it. Thus, while parallel code generation can improve build time, it can duplicate non-inlined, non-kernel functions across multiple partitions, potentially increasing the binary size of the final object file.
* Compiler option `-flto-partitions=<num>`:
Equivalent to the `--lto-partitions=<num>` LLD option. Controls the number of partitions used for parallel code generation when using full LTO (including when using `-fgpu-rdc`). The number of partitions must be greater than 0, and a value of 1 turns off the feature. The default value is 8.
* Compiler option `-flto-partitions=<num>` is equivalent to the `--lto-partitions=<num>` LLD option. Controls the number of partitions used for parallel code generation when using full LTO (including when using `-fgpu-rdc`). The number of partitions must be greater than 0, and a value of 1 turns off the feature. The default value is 8.
Developers are encouraged to experiment with different numbers of partitions using the `-flto-partitions` Clang command line option. Recommended values are 1 to 16 partitions, with especially large projects containing many kernels potentially benefiting from up to 64 partitions. It is not recommended to use a value greater than the number of threads on the machine. Smaller projects, or those containing only a few kernels, might not benefit at all from partitioning and might even experience a slight increase in build time due to the small overhead of analyzing and partitioning the modules.
Developers are encouraged to experiment with different numbers of partitions using the `-flto-partitions` Clang command line option. For experimentation, recommended values are 1 to 16 partitions, with especially large projects containing many kernels potentially benefiting from up to 64 partitions. It is not recommended to use a value greater than the number of threads on the machine. Smaller projects, or those containing only a few kernels, might not benefit at all from partitioning and might even experience a slight increase in build time due to the small overhead of analyzing and partitioning the modules.
* HIPIFY now supports NVIDIA CUDA 12.9.1 APIs:
* HIPIFY now supports CUDA 12.9.1 APIs:
* Added support for all new device and host APIs, including `FP4`, `FP6`, and `FP128`– including support for the corresponding ROCm HIP equivalents.
* The HIPCC Perl scripts (`hipcc.pl` and `hipconfig.pl`) have been removed in this release.
@@ -1312,7 +1310,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Changed
* The NVIDIA backend now requires CUB, Thrust, and libcu++ 2.7.0. If they aren't found, they will be downloaded from the NVIDIA CCCL repository.
* The CUDA backend now requires CUB, Thrust, and libcu++ 2.7.0. If they aren't found, they will be downloaded from the CUDA CCCL repository.
* Updated `thread_load` and `thread_store` to align hipCUB with CUB.
* All kernels now have hidden symbol visibility. All symbols now have inline namespaces that include the library version, (for example, `hipcub::HIPCUB_300400_NS::symbol` instead of `hipcub::symbol`), letting the user link multiple libraries built with different versions of hipCUB.
* Modified the broadcast kernel in warp scan benchmarks. The reported performance may be different to previous versions.
@@ -1336,7 +1334,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Known issues
* `BlockAdjacentDifference::FlagHeads`, `BlockAdjacentDifference::FlagTails` and `BlockAdjacentDifference::FlagHeadsAndTails` have been removed from hipCUB's CUB backend. They were already deprecated as of version 2.12.0 of hipCUB and they were removed from CCCL (CUB) as of CCCL's 2.6.0 release.
* `BlockScan::InclusiveScan` for the NVIDIA backend does not compute the block aggregate correctly when passing an initial value parameter. This behavior is not matched by the AMD backend.
* `BlockScan::InclusiveScan` for the CUDA backend does not compute the block aggregate correctly when passing an initial value parameter. This behavior is not matched by the AMD backend.
#### Upcoming changes
@@ -1358,7 +1356,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Added
* Documentation clarifying how hipfort is built for the NVIDIA platform.
* Documentation clarifying how hipfort is built for the CUDA platform.
#### Changed
@@ -1405,7 +1403,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Resolved issues
* Corrected the value of `lwork` returned by various `bufferSize` functions to be consistent with NVIDIA cuSOLVER. The following functions now return `lwork` so that the workspace size (in bytes) is `sizeof(T) * lwork`, rather than `lwork`. To restore the original behavior, set the environment variable `HIPSOLVER_BUFFERSIZE_RETURN_BYTES`.
* Corrected the value of `lwork` returned by various `bufferSize` functions to be consistent with CUDA cuSOLVER. The following functions now return `lwork` so that the workspace size (in bytes) is `sizeof(T) * lwork`, rather than `lwork`. To restore the original behavior, set the environment variable `HIPSOLVER_BUFFERSIZE_RETURN_BYTES`.
* `hipsolverXorgbr_bufferSize`, `hipsolverXorgqr_bufferSize`, `hipsolverXorgtr_bufferSize`, `hipsolverXormqr_bufferSize`, `hipsolverXormtr_bufferSize`, `hipsolverXgesvd_bufferSize`, `hipsolverXgesvdj_bufferSize`, `hipsolverXgesvdBatched_bufferSize`, `hipsolverXgesvdaStridedBatched_bufferSize`, `hipsolverXsyevd_bufferSize`, `hipsolverXsyevdx_bufferSize`, `hipsolverXsyevj_bufferSize`, `hipsolverXsyevjBatched_bufferSize`, `hipsolverXsygvd_bufferSize`, `hipsolverXsygvdx_bufferSize`, `hipsolverXsygvj_bufferSize`, `hipsolverXsytrd_bufferSize`, `hipsolverXsytrf_bufferSize`.
### **hipSPARSE** (4.0.1)
@@ -1433,7 +1431,7 @@ HIP runtime has the following functional improvements which improves runtime per
#### Known issues
* In `hipsparseSpSM_solve()`, the external buffer is passed as a parameter. This does not match the NVIDIA CUDA cuSPARSE API. This extra external buffer parameter will be removed in a future release. For now, this extra parameter can be ignored and nullptr passed in because it is unused internally.
* In `hipsparseSpSM_solve()`, the external buffer is passed as a parameter. This does not match the CUDA cuSPARSE API. This extra external buffer parameter will be removed in a future release. For now, this extra parameter can be ignored and nullptr passed in because it is unused internally.
### **hipSPARSELt** (0.2.4)
@@ -1507,7 +1505,7 @@ HIP runtime has the following functional improvements which improves runtime per
* `llvm-flang`, AMD's next-generation Fortran compiler. It's a re-implementation of the Fortran frontend that can be found at `llvm/llvm-project/flang` on GitHub.
* Comgr support for an in-memory virtual file system (VFS) for storing temporary files generated during intermediate compilation steps to improve performance in the device library link step.
* Compiler support of a new target-specific builtin `__builtin_amdgcn_processor_is` for late or deferred queries of the current target processor, and `__builtin_amdgcn_is_invocable` to determine the current target processor ability to invoke a particular builtin.
* HIPIFY support for NVIDIA CUDA 12.9.1 APIs. Added support for all new device and host APIs, including FP4, FP6, and FP128, and support for the corresponding ROCm HIP equivalents.
* HIPIFY support for CUDA 12.9.1 APIs. Added support for all new device and host APIs, including FP4, FP6, and FP128, and support for the corresponding ROCm HIP equivalents.
#### Changed

12
docs/compatibility/compatibility-matrix.rst
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@@ -29,12 +29,12 @@ compatibility and system requirements.
:ref:`Operating systems & kernels <OS-kernel-versions>`,Ubuntu 24.04.3,Ubuntu 24.04.2,Ubuntu 24.04.2
,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5
,"RHEL 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.5, 9.4"
,RHEL 8.10,RHEL 8.10,RHEL 8.10
,RHEL 8.10 [#rhel-700]_,RHEL 8.10 [#rhel-700],RHEL 8.10 [#rhel-700]
,SLES 15 SP7,"SLES 15 SP7, SP6","SLES 15 SP6, SP5"
,"Oracle Linux 9, 8 [#ol-700-mi300x]_","Oracle Linux 9, 8 [#ol-mi300x]_",Oracle Linux 8.10 [#ol-mi300x]_
,Debian 12,Debian 12 [#single-node]_,
,Azure Linux 3.0 [#az-mi300x]_,Azure Linux 3.0 [#az-mi300x]_,
,Rocky Linux 9,,
,Rocky Linux 9 [#rl-700]_,,
,.. _architecture-support-compatibility-matrix:,,
:doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA4,,
,CDNA3,CDNA3,CDNA3
@@ -158,8 +158,12 @@ compatibility and system requirements.
.. rubric:: Footnotes
.. [#ol-700-mi300x] **For ROCm 7.0.0** - Oracle Linux 9 is supported only on AMD Instinct MI300X, MI350X, and MI355X. Oracle Linux 8 is only supported on AMD Instinct MI300X.
.. [#ol-mi300x] **Prior to ROCm 7.0.0** - Oracle Linux is supported only on AMD Instinct MI300X.
.. [#rhel-700] RHEL 8.10 is only supported on AMD Instinct MI300X, MI300A, MI250X, MI250, MI210, and MI100 GPUs.
.. [#ol-700-mi300x] **For ROCm 7.0** - Oracle Linux 9 is supported only on AMD Instinct MI300X, MI350X, and MI355X. Oracle Linux 8 is only supported on AMD Instinct MI300X.
.. [#ol-mi300x] **Prior ROCm 7.0** - Oracle Linux is supported only on AMD Instinct MI300X.
.. [#sles-db-700] SLES 15 SP7 and Debian 12 are only supported on AMD Instinct MI300X, MI300A, MI250X, MI250, and MI210 GPUs.
.. [#az-mi300x] Starting ROCm 6.4.0, Azure Linux 3.0 is supported only on AMD Instinct MI300X and AMD Radeon PRO V710.
.. [#rl-700] Rocky Linux 9 is only supported on AMD Instinct MI300X and MI300A GPUs.
.. [#single-node] **Prior to ROCm 7.0.0** - Debian 12 is supported only on AMD Instinct MI300X for single-node functionality.
.. [#az-mi300x] Starting from ROCm 6.4.0, Azure Linux 3.0 is supported only on AMD Instinct MI300X and AMD Radeon PRO V710.
.. [#RDNA-OS] Radeon AI PRO R9700, Radeon RX 9070 XT (gfx1201), Radeon RX 9060 XT (gfx1200), Radeon PRO W7700 (gfx1101), and Radeon RX 7800 XT (gfx1101) are supported only on Ubuntu 24.04.2, Ubuntu 22.04.5, RHEL 9.6, and RHEL 9.4.