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amd/jayhaw
| Author | SHA1 | Date | |
|---|---|---|---|
|
febbf385c4 |
@@ -32,6 +32,7 @@ parameters:
|
||||
- name: aptPackages
|
||||
type: object
|
||||
default:
|
||||
- cmake
|
||||
- gfortran
|
||||
- git
|
||||
- libboost-program-options-dev
|
||||
@@ -41,7 +42,6 @@ parameters:
|
||||
- name: rocmDependencies
|
||||
type: object
|
||||
default:
|
||||
- aomp
|
||||
- clr
|
||||
- llvm-project
|
||||
- rocminfo
|
||||
@@ -51,7 +51,6 @@ parameters:
|
||||
- name: rocmTestDependencies
|
||||
type: object
|
||||
default:
|
||||
- aomp
|
||||
- clr
|
||||
- llvm-project
|
||||
- hipBLAS-common
|
||||
@@ -104,7 +103,6 @@ jobs:
|
||||
parameters:
|
||||
aptPackages: ${{ parameters.aptPackages }}
|
||||
packageManager: ${{ job.packageManager }}
|
||||
- template: ${{ variables.CI_TEMPLATE_PATH }}/steps/dependencies-cmake-custom.yml
|
||||
- template: ${{ variables.CI_TEMPLATE_PATH }}/steps/preamble.yml
|
||||
- template: ${{ variables.CI_TEMPLATE_PATH }}/steps/checkout.yml
|
||||
parameters:
|
||||
@@ -130,7 +128,6 @@ jobs:
|
||||
-DCMAKE_PREFIX_PATH=$(Agent.BuildDirectory)/rocm;$(Agent.BuildDirectory)/vendor
|
||||
-DCMAKE_CXX_COMPILER=$(Agent.BuildDirectory)/rocm/llvm/bin/amdclang++
|
||||
-DCMAKE_C_COMPILER=$(Agent.BuildDirectory)/rocm/bin/amdclang
|
||||
-DCMAKE_Fortran_COMPILER=gfortran
|
||||
-DCMAKE_BUILD_TYPE=Release
|
||||
-DBUILD_CLIENTS_TESTS=ON
|
||||
-DBUILD_CLIENTS_SAMPLES=OFF
|
||||
|
||||
@@ -60,7 +60,6 @@ parameters:
|
||||
- rocprofiler-register
|
||||
- ROCR-Runtime
|
||||
- roctracer
|
||||
- rocSPARSE
|
||||
- name: rocmTestDependencies
|
||||
type: object
|
||||
default:
|
||||
@@ -75,7 +74,6 @@ parameters:
|
||||
- rocprofiler-register
|
||||
- ROCR-Runtime
|
||||
- roctracer
|
||||
- rocSPARSE
|
||||
|
||||
- name: jobMatrix
|
||||
type: object
|
||||
|
||||
@@ -36,7 +36,6 @@ Andrej
|
||||
Arb
|
||||
Autocast
|
||||
autograd
|
||||
Backported
|
||||
BARs
|
||||
BatchNorm
|
||||
BLAS
|
||||
@@ -204,11 +203,9 @@ GenAI
|
||||
GenZ
|
||||
GitHub
|
||||
Gitpod
|
||||
hardcoded
|
||||
HBM
|
||||
HCA
|
||||
HGX
|
||||
HLO
|
||||
HIPCC
|
||||
hipDataType
|
||||
HIPExtension
|
||||
@@ -336,7 +333,6 @@ MoEs
|
||||
Mooncake
|
||||
Mpops
|
||||
Multicore
|
||||
multihost
|
||||
Multithreaded
|
||||
mx
|
||||
MXFP
|
||||
@@ -1031,7 +1027,6 @@ uncacheable
|
||||
uncorrectable
|
||||
underoptimized
|
||||
unhandled
|
||||
unfused
|
||||
uninstallation
|
||||
unmapped
|
||||
unsqueeze
|
||||
|
||||
683
CHANGELOG.md
683
CHANGELOG.md
@@ -4,689 +4,6 @@ This page is a historical overview of changes made to ROCm components. This
|
||||
consolidated changelog documents key modifications and improvements across
|
||||
different versions of the ROCm software stack and its components.
|
||||
|
||||
## ROCm 7.2.0
|
||||
|
||||
See the [ROCm 7.2.0 release notes](https://rocm.docs.amd.com/en/docs-7.2.0/about/release-notes.html#rocm-7-2-0-release-notes)
|
||||
for a complete overview of this release.
|
||||
|
||||
### **AMD SMI** (26.2.1)
|
||||
|
||||
#### Added
|
||||
|
||||
- GPU and baseboard temperature options to `amd-smi monitor` CLI.
|
||||
- `amd-smi monitor --gpu-board-temps` for GPU board temperature sensors.
|
||||
- `amd-smi monitor --base-board-temps` for base board temperature sensors.
|
||||
|
||||
(amdsmi-npm-changelog)=
|
||||
- New Node Power Management (NPM) APIs and CLI options for node monitoring.
|
||||
- C++ API functions:
|
||||
- `amdsmi_get_node_handle()` gets the handle for a node device.
|
||||
- `amdsmi_get_npm_info()` retrieves Node Power Management information.
|
||||
- C++ types:
|
||||
- `amdsmi_npm_status_t` indicates whether NPM is enabled or disabled.
|
||||
- `amdsmi_npm_info_t` contains the status and node-level power limit in watts.
|
||||
- Added Python API wrappers for new node device functions.
|
||||
- Added `amd-smi node` subcommand for NPM operations via CLI.
|
||||
- Currently supported for `OAM_ID 0` only.
|
||||
|
||||
- The following C APIs are added to `amdsmi_interface.py`:
|
||||
- `amdsmi_get_cpu_handle()`
|
||||
- `amdsmi_get_esmi_err_msg()`
|
||||
- `amdsmi_get_gpu_event_notification()`
|
||||
- `amdsmi_get_processor_count_from_handles()`
|
||||
- `amdsmi_get_processor_handles_by_type()`
|
||||
- `amdsmi_gpu_validate_ras_eeprom()`
|
||||
- `amdsmi_init_gpu_event_notification()`
|
||||
- `amdsmi_set_gpu_event_notification_mask()`
|
||||
- `amdsmi_stop_gpu_event_notification()`
|
||||
- `amdsmi_get_gpu_busy_percent()`
|
||||
|
||||
- Additional return value to `amdsmi_get_xgmi_plpd()` API:
|
||||
- The entry `policies` is added to the end of the dictionary to match API definition.
|
||||
- The entry `plpds` is marked for deprecation as it has the same information as `policies`.
|
||||
|
||||
- PCIe levels to `amd-smi static --bus` command.
|
||||
- The static `--bus` option has been updated to include the range of PCIe levels that you can set for a device.
|
||||
- Levels are a 2-tuple composed of the PCIe speed and bandwidth.
|
||||
|
||||
- `evicted_time` metric for KFD processes.
|
||||
- Time that queues are evicted on a GPU in milliseconds.
|
||||
- Added to CLI in `amd-smi monitor -q` and `amd-smi process`.
|
||||
- Added to C APIs and Python APIs: `amdsmi_get_gpu_process_list()`, `amdsmi_get_gpu_compute_process_info()`
|
||||
, and `amdsmi_get_gpu_compute_process_info_by_pid()`.
|
||||
|
||||
- New VRAM types to `amdsmi_vram_type_t`.
|
||||
- `amd-smi static --vram` and `amdsmi_get_gpu_vram_info()` now support the following types: `DDR5`, `LPDDR4`, `LPDDR5`, and `HBM3E`.
|
||||
|
||||
- Support for PPT1 power limit information.
|
||||
- Support has been added for querying and setting the PPT (Package Power Tracking) limits.
|
||||
- There are two PPT limits. PPT0 has lower limit and tracks a filtered version of the input power. PPT1 has higher limit but tracks the raw input power. This is to catch spikes in the raw data.
|
||||
- New API added:
|
||||
- `amdsmi_get_supported_power_cap()`: Returns power cap types supported on the device (PPT0, PPT1). This will allow you to know which power cap types you can get/set.
|
||||
- Original APIs remain the same but now can get/set both PPT0 and PPT1 limits (on supported hardware): `amdsmi_get_power_cap_info()` and `amdsmi_set_power_cap()`.
|
||||
- See the Changed section for changes made to the `set` and `static` commands regarding support for PPT1.
|
||||
|
||||
#### Changed
|
||||
|
||||
- The `amd-smi` command now shows `hsmp` rather than `amd_hsmp`.
|
||||
- The `hsmp` driver version can be shown without the `amdgpu` version using `amd-smi version -c`.
|
||||
|
||||
- The `amd-smi set --power-cap` command now requires specification of the power cap type.
|
||||
- Command now takes the form: `amd-smi set --power-cap <power-cap-type> <new-cap>`.
|
||||
- Acceptable power cap types are "ppt0" and "ppt1".
|
||||
|
||||
- The `amd-smi reset --power-cap` command will now attempt to reset both `PPT0` and `PPT1` power caps to their default values. If a device only has `PPT0`, then only `PPT0` will be reset.
|
||||
|
||||
- The `amd-smi static --limit` command now has a `PPT1` section when PPT1 is available. The `static --limit` command has been updated to include `PPT1` power limit information when available on the device.
|
||||
|
||||
#### Resolved Issues
|
||||
|
||||
- Fixed an issue where `amdsmi_get_gpu_od_volt_info()` returned a reference to a Python object. The returned dictionary was changed to return values in all fields.
|
||||
|
||||
### **Composable Kernel** (1.2.0)
|
||||
|
||||
#### Added
|
||||
* Support for mixed precision fp8 x bf8 universal GEMM and weight preshuffle GEMM.
|
||||
* Compute async pipeline in the CK Tile universal GEMM on gfx950.
|
||||
* Support for B Tensor type `pk_int4_t` in the CK Tile weight preshuffle GEMM.
|
||||
* New call to load different memory sizes to SGPR.
|
||||
* Support for B Tensor Preshuffle in CK Tile Grouped GEMM.
|
||||
* Basic copy kernel example and supporting documentation for new CK Tile developers.
|
||||
* Support for `grouped_gemm` kernels to perform `multi_d` elementwise operation.
|
||||
* Support for Multiple ABD GEMM.
|
||||
* Benchmarking support for tile engine GEMM Multi D.
|
||||
* Block scaling support in CK Tile GEMM, allowing flexible use of quantization matrices from either A or B operands.
|
||||
* Row-wise and column-wise quantization for CK Tile GEMM and grouped GEMM.
|
||||
* Support for `f32` to FMHA (fwd/bwd).
|
||||
* Tensor-wise quantization for CK Tile GEMM.
|
||||
* Support for batched contraction kernel.
|
||||
* WMMA (gfx12) support for FMHA.
|
||||
* Pooling kernel in CK Tile.
|
||||
* Top-k sigmoid kernel in CK Tile.
|
||||
* Blockscale 2D support for CK Tile GEMM.
|
||||
* An optional template parameter, `Arch`, to `make_kernel` to support linking multiple object files that have the same kernel compiled for different architectures.
|
||||
|
||||
#### Changed
|
||||
|
||||
* Removed `BlockSize` in `make_kernel` and `CShuffleEpilogueProblem` to support Wave32 in CK Tile.
|
||||
* FMHA examples and tests can be built for multiple architectures (gfx9, gfx950, gfx12) at the same time.
|
||||
|
||||
#### Upcoming changes
|
||||
|
||||
* Composable Kernel will be adopting C++20 features in an upcoming ROCm release, updating the minimum compiler requirement to C++20. Ensure that your development environment complies with this requirement to facilitate a seamless transition.
|
||||
* In an upcoming major ROCm release, Composable Kernel will transition to a header-only library. Neither ckProfiler nor the static libraries will be packaged with Composable Kernel. They will also no longer be built by default. ckProfiler can be built independently from Composable Kernel as a standalone binary, and the static Composable Kernel libraries can be built from source.
|
||||
|
||||
### **HIP** (7.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* New HIP APIs
|
||||
- `hipLibraryEnumerateKernels` returns kernel handles within a library.
|
||||
- `hipKernelGetLibrary` returns library handle for a hipKernel_t handle.
|
||||
- `hipKernelGetName` returns function name for a hipKernel_t handle.
|
||||
- `hipLibraryLoadData` creates library object from code.
|
||||
- `hipLibraryLoadFromFile` creates library object from file.
|
||||
- `hipLibraryUnload` unloads library.
|
||||
- `hipLibraryGetKernel` gets a kernel from the library.
|
||||
- `hipLibraryGetKernelCount` gets kernel count in library.
|
||||
- `hipStreamCopyAttributes` copies attributes from source stream to destination stream.
|
||||
- `hipOccupancyAvailableDynamicSMemPerBlock` returns dynamic shared memory available per block when launching numBlocks blocks on CU.
|
||||
* New HIP flags
|
||||
- `hipMemLocationTypeHost` enables handling virtual memory management in host memory location, in addition to device memory.
|
||||
- Support for flags in `hipGetProcAddress` enables searching for the per-thread version symbols:
|
||||
- `HIP_GET_PROC_ADDRESS_DEFAULT`
|
||||
- `HIP_GET_PROC_ADDRESS_LEGACY_STREAM`
|
||||
- `HIP_GET_PROC_ADDRESS_PER_THREAD_DEFAULT_STREAM`
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Graph node scaling:
|
||||
- HIP runtime implements an optimized doorbell ring mechanism for certain topologies of graph execution. It enables efficient batching of graph nodes.
|
||||
- The enhancement provides better alignment with CUDA Graph optimizations.
|
||||
- HIP also adds a new performance test for HIP graphs with programmable topologies to measure graph performance across different structures.
|
||||
- The test evaluates graph instantiation time, first launch time, repeat launch times, and end-to-end execution for various graph topologies.
|
||||
- The test implements comprehensive timing measurements including CPU overhead and device execution time.
|
||||
* Back memory set (memset) optimization:
|
||||
- HIP runtime now implements a back memory set (memset) optimization to improve how memset nodes are processed during graph execution.
|
||||
- The enhancement specifically handles varying number of Architected Queue Language (AQL) packets for memset graph node due to graph node set params for AQL batch submission approach.
|
||||
* Async handler performance improvement:
|
||||
- HIP runtime has removed the lock contention in async handler enqueue path.
|
||||
- - The enhancement reduces runtime overhead and maximizes GPU throughput for asynchronous kernel execution, especially in multi-threaded applications.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Corrected the calculation of the value of maximum shared memory per multiprocessor, in HIP device properties.
|
||||
|
||||
### **hipBLAS** (3.2.0)
|
||||
|
||||
#### Resolved issues
|
||||
* Corrected client memory use counts for the `HIPBLAS_CLIENT_RAM_GB_LIMIT` environment variable.
|
||||
* Fixed false Clang static analysis warnings.
|
||||
|
||||
### **hipBLASLt** (1.2.1)
|
||||
|
||||
#### Added
|
||||
|
||||
* Support for the `BF16` input data type with an `FP32` output data type for gfx90a.
|
||||
* Support for hipBLASLtExt operation APIs on gfx11XX and gfx12XX.
|
||||
* `HIPBLASLT_OVERRIDE_COMPUTE_TYPE_XF32` to override the compute type from `xf32` to other compute types.
|
||||
* Support for the Sigmoid Activation function.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Fixed the `HIPBLAS_STATUS_INTERNAL_ERROR` issue that could occur with various sizes in CPX mode.
|
||||
|
||||
### **hipCUB** (4.2.0)
|
||||
|
||||
#### Added
|
||||
* Experimental SPIR-V support.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Fixed memory leak issues with some unit tests.
|
||||
|
||||
### **hipFFT** (1.0.22)
|
||||
|
||||
#### Added
|
||||
|
||||
* hipFFTW execution functions, where input and output data buffers differ from the
|
||||
buffers specified at plan creation:
|
||||
|
||||
* fftw_execute_dft
|
||||
* fftwf_execute_dft
|
||||
* fftw_execute_dft_r2c
|
||||
* fftwf_execute_dft_r2c
|
||||
* fftw_execute_dft_c2r
|
||||
* fftwf_execute_dft_c2r
|
||||
|
||||
### **HIPIFY** (22.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Partial support for CUDA 13.0.0 support.
|
||||
* cuDNN 9.14.0 support.
|
||||
* cuTENSOR 2.3.1.0 support.
|
||||
* LLVM 21.1.6 support.
|
||||
* Full `hipFFTw` support.
|
||||
* [#2062](https://github.com/ROCm/HIPIFY/issues/2062) Partial hipification support for a particular CUDA API.
|
||||
* [#2073](https://github.com/ROCm/HIPIFY/issues/2073) Detect CUDA version before hipification.
|
||||
* New options:
|
||||
* `--local-headers` to enable hipification of quoted local headers (non-recursive).
|
||||
* `--local-headers-recursive` to enable hipification of quoted local headers recursively.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* [#2088](https://github.com/ROCm/HIPIFY/issues/2088) Missing support of `cuda_bf16.h` import in hipification.
|
||||
|
||||
### **hipSOLVER** (3.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Ability to control rocSOLVER logging using the environment variables `ROCSOLVER_LEVELS` and `ROCSOLVER_LAYER`.
|
||||
|
||||
### **hipSPARSE** (4.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* `--clients-only` option to the `install.sh` and `rmake.py` scripts for building only the clients when using a version of hipSPARSE that is already installed.
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Improved the user documentation.
|
||||
|
||||
#### Resolved Issues
|
||||
|
||||
* Fixed a memory leak in the `hipsparseCreate` functions.
|
||||
|
||||
### **hipSPARSELt** (0.2.6)
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Provided more kernels for the `FP16` and `FP8(E4M3)` data types.
|
||||
|
||||
### **hipTensor** (2.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Software-managed plan cache support.
|
||||
* `hiptensorHandleWritePlanCacheToFile` to write the plan cache of a hipTensor handle to a file.
|
||||
* `hiptensorHandleReadPlanCacheFromFile` to read a plan cache from a file into a hipTensor handle.
|
||||
* `simple_contraction_plan_cache` to demonstrate plan cache usages.
|
||||
* `plan_cache_test` to test the plan cache across various tensor ranks.
|
||||
* C API headers to enable compatibility with C programs.
|
||||
* A CMake function to allow projects to query architecture support.
|
||||
* An option to configure the memory layout for tests and benchmarks.
|
||||
|
||||
#### Changed
|
||||
|
||||
* hipTensor has been moved into the new rocm-libraries "monorepo" repository {fab}`github` [rocm-libraries](https://github.com/ROCm/rocm-libraries). This repository consolidates a number of separate ROCm libraries and shared components.
|
||||
* The repository migration requires a few changes to the CMake configuration of hipTensor.
|
||||
* Updated C++ standard from C++17 to C++20.
|
||||
* Include files `hiptensor/hiptensor.hpp` and `hiptensor/hiptensor_types.hpp` are now deprecated. Use `hiptensor/hiptensor.h` and `hiptensor/hiptensor_types.h` instead.
|
||||
* Converted include guards from #ifndef/#define/#endif to #pragma once.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Removed large tensor sizes causing problem in benchmarks.
|
||||
|
||||
### **llvm-project** (22.0.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Enabled ThinLTO for ROCm compilers using `-foffload-lto=thin`. For more information, see [ROCm compiler reference](https://rocm.docs.amd.com/projects/llvm-project/en/docs-7.2.0/reference/rocmcc.html#amd-gpu-compilation).
|
||||
|
||||
#### Changed
|
||||
|
||||
* Updated clang/llvm to AMD clang version 22.0.0 (equivalent to LLVM 22.0.0 with additional out-of-tree patches).
|
||||
|
||||
### **MIGraphX** (2.15.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* MXFP4 support for Quark and Brevitas quantized models.
|
||||
* Dynamic shape support for `DepthToSpace Op`.
|
||||
* `bias` and `key_mask_padding` inputs for the `MultiHeadAttention` operator.
|
||||
* GEMM+GEMM fusions.
|
||||
* `dim_params` input parameter to the `parse_onnx` Python call.
|
||||
* Created an API to query supported ONNX Operators `get_onnx_operators()`.
|
||||
* Right pad masking mode for Multihead Attention.
|
||||
* Support for Flash Decoding.
|
||||
* Torch-MIGraphX installation instructions.
|
||||
* Operator Builders with supporting documentation.
|
||||
* Index range check to the Gather operator.
|
||||
|
||||
#### Changed
|
||||
|
||||
* Updated the Resize operator to support linear mode for Dynamic shapes.
|
||||
* Switched to `--input-dim` instead of `--batch` to set any dynamic dimensions when using `migraphx-driver`.
|
||||
* Different stride sizes are now supported in ONNX `if` branches.
|
||||
* ONNX version change to 1.18.0 to support PyTorch 2.9.1.
|
||||
* Refactored `GroupQueryAttention`.
|
||||
* Enabled `PipelineRepoRef` parameter in CI.
|
||||
* Hide LLVM symbols that come from ROCmlir and provide option for stripping in release mode.
|
||||
* Model compilation failures now produce an mxr file for debugging the failure.
|
||||
* Bumped SQlite3 to 3.50.4.
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Converted the `LRN` operator to an optimized `pooling` operator.
|
||||
* Streamlined the `find_matches` function.
|
||||
* Reduced the number of splits used for `split_reduce`.
|
||||
* Improved layout propagation in pointwise fusion when using broadcasted inputs.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Quiet nrvo and noreturn warnings.
|
||||
* Fixed `pointwise: Wrong number of arguments` error when quantizing certain models to `int8`.
|
||||
* TopK exception bugfix.
|
||||
* Updated SD3 example for change in optimum-onnx[onnxruntime].
|
||||
* Fixed an issue with Torch-MIGraphX where the model compilation would fail.
|
||||
* Fixed an issue where a reduction was broadcast with different dimensions than the input.
|
||||
* Resolved a path name issue stopping some files being created on Windows for debugging.
|
||||
* Fixed "reduce_sum: axes: value out of range" error in `simplify_reshapes`.
|
||||
* Updated README `rbuild` installation instructions to use Python venv to avoid warning.
|
||||
* Ensured directories exist when generating files for debugging.
|
||||
* Resolved a compilation hang issue.
|
||||
|
||||
### **MIOpen** (3.5.1)
|
||||
|
||||
#### Added
|
||||
* 3D heuristics for gfx950.
|
||||
* Optional timestamps to MIOpen logging.
|
||||
* Option to log when MIOpen starts and finishes tuning.
|
||||
* Winograd Fury 4.6.0 for gfx12 for improved convolution performance.
|
||||
|
||||
#### Changed
|
||||
* Ported several OCL kernels to HIP.
|
||||
|
||||
#### Optimized
|
||||
* Improved Composable Kernel (CK) kernel selection during tuning.
|
||||
* Improved user DB file locking to better handle network storage.
|
||||
* Improved performance for MIOpen check numerics capabilities.
|
||||
|
||||
#### Resolved issues
|
||||
* Addressed an issue in the stride adjustment logic for ASM (MISA) kernels when the output dimension is one.
|
||||
* Fixed an issue with the CK bwd solver applicability checks when deterministic is set.
|
||||
* [BatchNorm] Fixed issue where batchnorm tuning would give incorrect results.
|
||||
* Fixed issue where generic search was not providing sufficient warm-up for some kernels.
|
||||
|
||||
### **MIVisionX** (3.5.0)
|
||||
|
||||
#### Changed
|
||||
|
||||
* AMD Clang++ location updated to `${ROCM_PATH}/lib/llvm/bin`.
|
||||
* Required RPP version updated to RPP V2.2.1.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Memory leaks in OpenVX core, vx_nn, & vx_opencv.
|
||||
|
||||
#### Known issues
|
||||
|
||||
* Installation on RedHat and SLES requires the manual installation of the FFmpeg and OpenCV dev packages.
|
||||
|
||||
#### Upcoming changes
|
||||
|
||||
* VX_AMD_MEDIA - `rocDecode` and `rocJPEG` support for hardware decode.
|
||||
|
||||
### **RCCL** (2.27.7)
|
||||
|
||||
#### Changed
|
||||
|
||||
* RCCL error messages have been made more verbose in several cases. RCCL now prints out fatal error messages by default. Fatal error messages can be suppressed by setting `NCCL_DEBUG=NONE`.
|
||||
* Disabled `reduceCopyPacks` pipelining for `gfx950`.
|
||||
|
||||
### **rocAL** (2.5.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* `EnumRegistry` to register all the enums present in rocAL.
|
||||
* `Argument` class which stores the value and type of each argument in the Node.
|
||||
* `PipelineOperator` class to represent operators in the pipeline with metadata.
|
||||
* Support to track operators in MasterGraph with unique naming.
|
||||
|
||||
#### Changed
|
||||
|
||||
* OpenCL backend support is deprecated.
|
||||
* CXX Compiler: Use AMDClang++ compiler core location `${ROCM_PATH}/lib/llvm/bin`.
|
||||
* Refactored external enum usage in rocAL to maintain separation between external and internal enums.
|
||||
* Introduced the following enums `ResizeScalingMode`, `ResizeInterpolationType`, `MelScaleFormula`, `AudioBorderType`, and `OutOfBoundsPolicy` in `commons.h`.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Use HIP memory for fused crop rocJPEG decoder.
|
||||
* Issue in numpy loader where ROI is updated incorrectly.
|
||||
* Issue in CropResize node where `crop_w` and `crop_h` values were not correctly updated.
|
||||
|
||||
#### Known issues
|
||||
|
||||
* Package installation on SLES requires manually installing `TurboJPEG`.
|
||||
* Package installation on RedHat and SLES requires manually installing the FFmpeg dev package.
|
||||
|
||||
### **rocALUTION** (4.1.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* `--clients-only` option to the `install.sh` and `rmake.py` scripts to allow building only the clients while using an already installed version of rocALUTION.
|
||||
|
||||
### **rocBLAS** (5.2.0)
|
||||
|
||||
#### Added
|
||||
* Level 3 `syrk_ex` function for both C and FORTRAN, without API support for the ILP64 format.
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Level 2 `tpmv` and `sbmv` functions.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Corrected client memory use counts for the `ROCBLAS_CLIENT_RAM_GB_LIMIT` environment variable.
|
||||
* Fixed false Clang static analysis warnings.
|
||||
|
||||
### **rocDecode** (1.5.0)
|
||||
|
||||
#### Added
|
||||
* Logging control. Message output from the core components is now controlled by the logging level threshold, which can be set by an environment variable or other methods.
|
||||
* The new `rocdecode-host` package must be installed to use the FFmpeg decoder.
|
||||
|
||||
#### Changed
|
||||
|
||||
* Updated `libdrm` path configuration and `libva` version requirements for ROCm and TheRock platforms.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Fixed the build error with videodecodepicfiles sample.
|
||||
* Added error handling of sample app command option combination of memory type OUT_SURFACE_MEM_NOT_MAPPED and MD5 generation.
|
||||
|
||||
### **rocFFT** (1.0.36)
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Removed a potentially unnecessary global transpose operation from MPI 3D multi-GPU pencil decompositions.
|
||||
* Enabled optimization of 3D pencil decompositions for single-process multi-GPU transforms.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Fixed potential division by zero when constructing plans using dimensions of length 1.
|
||||
* Fixed result scaling on multi-device transforms.
|
||||
* Fixed callbacks on multi-device transforms.
|
||||
|
||||
### **rocJPEG** (1.3.0)
|
||||
|
||||
#### Changed
|
||||
|
||||
* Updated `libdrm` path configuration and `libva` version requirements for ROCm and TheRock platforms.
|
||||
* RHEL now uses `libva-devel` instead of `libva-amdgpu`/`libva-amdgpu-devel`.
|
||||
* Use ROCm clang++ from `${ROCM_PATH}/lib/llvm/bin` location.
|
||||
|
||||
### **ROCm Bandwidth Test** (2.6.0)
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* `rocm-bandwidth-test` folder is no longer present after driver uninstallation.
|
||||
|
||||
### **ROCm Compute Profiler** (3.4.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* `--list-blocks <arch>` option to general options. It lists the available IP blocks on the specified arch (similar to `--list-metrics`). However, cannot be used with `--block`.
|
||||
|
||||
* `config_delta/gfx950_diff.yaml` to analysis config YAMLs to track the revision between the gfx9xx GPUs against the latest supported gfx950 GPUs.
|
||||
|
||||
* Analysis db features
|
||||
* Adds support for per kernel metrics analysis.
|
||||
* Adds support for dispatch timeline analysis.
|
||||
* Shows duration as median in addition to mean in kernel view.
|
||||
|
||||
* AMDGPU driver info and GPU VRAM attributes in the system info section of the analysis report.
|
||||
|
||||
* `CU Utilization` metric to display the percentage of CUs utilized during kernel execution.
|
||||
|
||||
#### Changed
|
||||
|
||||
* `-b/--block` accepts block alias(es). See block aliases using command-line option `--list-blocks <arch>`.
|
||||
|
||||
* Analysis configs YAMLs are now managed with the new config management workflow in `tools/config_management/`.
|
||||
|
||||
* `amdsmi` python API is used instead of `amd-smi` CLI to query GPU specifications.
|
||||
|
||||
* Empty cells replaced with `N/A` for unavailable metrics in analysis.
|
||||
|
||||
#### Removed
|
||||
|
||||
* Removed `database` mode from ROCm Compute Profiler in favor of other visualization methods, rather than Grafana and MongoDB integration, such as the upcoming Analysis DB-based Visualizer.
|
||||
* Plotly server based standalone GUI.
|
||||
* Commandline based Textual User Interface.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Fixed issue of sL1D metric values displaying as `N/A` in memory chart diagram.
|
||||
|
||||
#### Upcoming changes
|
||||
|
||||
* `Active CUs` metric has been deprecated in favor of `CU Utilization` and will be removed in a future release.
|
||||
|
||||
### **ROCm Systems Profiler** (1.3.0)
|
||||
|
||||
#### Added
|
||||
|
||||
- `ROCPROFSYS_PERFETTO_FLUSH_PERIOD_MS` configuration setting to set the flush period for Perfetto traces. The default value is 10000 ms (10 seconds).
|
||||
- Fetching of the `rocpd` schema from rocprofiler-sdk-rocpd.
|
||||
|
||||
#### Changed
|
||||
|
||||
- Improved Fortran main function detection to ensure `rocprof-sys-instrument` uses the Fortran program main function instead of the C wrapper.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
- Fixed a crash when running `rocprof-sys-python` with ROCPROFSYS_USE_ROCPD enabled.
|
||||
- Fixed an issue where kernel/memory-copy events could appear on the wrong Perfetto track (e.g., queue track when stream grouping was requested) because _group_by_queue state leaked between records.
|
||||
- Fixed a soft hang in collecting available PAPI metrics on some systems with Intel CPU.
|
||||
- Fixed some duplicate HIP and HSA API events in `rocpd` output.
|
||||
|
||||
### **rocPRIM** (4.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Missing benchmarks, such that every autotuned specialization is now benchmarked.
|
||||
* A new cmake option, `BENCHMARK_USE_AMDSMI`. It is set to `OFF` by default. When this option is set to `ON`, it lets benchmarks use AMD SMI to output more GPU statistics.
|
||||
* The first tested example program for `device_search`.
|
||||
* `apply_config_improvements.py`file , which generates improved configs by taking the best specializations from old and new configs.
|
||||
* Run the script with `--help` for usage instructions, and see [rocPRIM Performance Tuning](https://rocm.docs.amd.com/projects/rocPRIM/en/latest/conceptual/rocPRIM-performance-tuning.html#rocprim-performance-tuning) for more information.
|
||||
* Kernel Tuner proof-of-concept.
|
||||
* Enhanced SPIR-V support and performance.
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Improved performance of `device_radix_sort` onesweep variant.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Fixed the issue where `rocprim::device_scan_by_key` failed when performing an "in-place" inclusive scan by reusing "keys" as output, by adding a buffer to store the last keys of each block (excluding the last block). This fix only affects the specific case of reusing "keys" as output in an inclusive scan, and does not affect other cases.
|
||||
* Fixed benchmark build error on Windows.
|
||||
* Fixed offload compress build option.
|
||||
* Fixed `float_bit_mask` for `rocprim::half`.
|
||||
* Fixed handling of undefined behaviour when `__builtin_clz`, `__builtin_ctz`, and similar builtins are called.
|
||||
* Fixed potential build error with `rocprim::detail::histogram_impl`.
|
||||
|
||||
#### Known issues
|
||||
|
||||
* Potential hang with `rocprim::partition_threeway` with large input data sizes on later ROCm builds. A workaround is currently in place.
|
||||
|
||||
### **ROCprofiler-SDK** (1.1.0)
|
||||
|
||||
#### Added
|
||||
|
||||
- Counter collection support for gfx1150 and gfx1151.
|
||||
- HSA Extension API v8 support.
|
||||
- `hipStreamCopyAttributes` API implementation.
|
||||
|
||||
#### Optimized
|
||||
|
||||
- Improved process attachment and updated the corresponding [documentation](https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/latest/how-to/using-rocprofv3-process-attachment.html).
|
||||
- Improved [Quick reference guide for rocprofv3](https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/latest/quick_guide.html).
|
||||
- Updated the [installation documentation](https://rocm.docs.amd.com/projects/rocprofiler-sdk/en/latest/install/installation.html) with the links to the latest repository.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
- Fixed multi-GPU dimension mismatch.
|
||||
- Fixed device lock issue for dispatch counters.
|
||||
- Addressed OpenMP Tools task scheduling null pointer exception.
|
||||
- Fixed stream ID errors arising during process attachment.
|
||||
- Fixed issues arising during dynamic code object loading.
|
||||
|
||||
### **rocPyDecode** (0.8.0)
|
||||
|
||||
#### Changed
|
||||
* CXX Compiler location - Use default `${ROCM_PATH}/lib/llvm/bin` for AMD Clang.
|
||||
|
||||
### **rocRAND** (4.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Added a new CMake option `-DUSE_SYSTEM_LIB` to allow tests to be built from `ROCm` libraries provided by the system.
|
||||
* Experimental SPIR-V support.
|
||||
|
||||
#### Changed
|
||||
|
||||
* The `launch` method in `host_system` and `device_system`, so that kernels with all supported arches can be compiled with correct configuration during host pass. All generators are updated accordingly for support of SPIR-V. To invoke SPIR-V, it should be built with `-DAMDGPU_TARGETS=amdgcnspirv`.
|
||||
|
||||
#### Removed
|
||||
|
||||
* For performance reasons, the `mrg31k3p_state`, `mrg32k3a_state`, `xorwow_state` and `philox4x32_10_state` states no longer use the `boxmuller_float_state` and `boxmuller_double_state` states, and the `boxmuller_float` and `boxmuller_double` variables are set with `NaN` as default values.
|
||||
|
||||
|
||||
### **rocSHMEM** (3.2.0)
|
||||
|
||||
#### Added
|
||||
* The GDA conduit for AMD Pensando IONIC.
|
||||
|
||||
#### Changed
|
||||
* Dependency libraries are now loaded dynamically.
|
||||
* The following APIs now have an implementation for the GDA conduit:
|
||||
* `rocshmem_p`
|
||||
* fetching atomics `rocshmem_<TYPE>_fetch_<op>`
|
||||
* collective APIs
|
||||
* The following APIs now have an implementation for the IPC conduit:
|
||||
* `rocshmem_<TYPE>_atomic_{and,or,xor,swap}`
|
||||
* `rocshmem_<TYPE>_atomic_fetch_{and,or,xor,swap}`
|
||||
|
||||
#### Known issues
|
||||
* Only 64-bit rocSHMEM atomic APIs are implemented for the GDA conduit.
|
||||
|
||||
### **rocSOLVER** (3.32.0)
|
||||
|
||||
#### Optimized
|
||||
|
||||
* Improved the performance of LARFB and downstream functions such as GEQRF and ORMTR.
|
||||
|
||||
### **rocSPARSE** (4.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Sliced ELL format support to the `rocsparse_spmv` routine.
|
||||
* The `rocsparse_sptrsv` and `rocsparse_sptrsm` routines for triangular solve.
|
||||
* The `--clients-only` option to the `install.sh` and `rmake.py` scripts to only build the clients for a version of rocSPARSE that is already installed.
|
||||
* NNZ split algorithm `rocsparse_spmv_alg_csr_nnzsplit` to `rocsparse_spmv`. This algorithm might be superior to the existing adaptive algorithm `rocsparse_spmv_alg_csr_adaptive` when running the computation a small number of times because it avoids paying the analysis cost of the adaptive algorithm.
|
||||
|
||||
#### Changed
|
||||
|
||||
* rocBLAS is a requirement when it's requested when building from source. Previously, rocBLAS was not used if it could not be found. To opt out of using rocBLAS when building from source, use the `--no-rocblas` option with the `install.sh` or `rmake.py` build scripts.
|
||||
|
||||
#### Optimized
|
||||
* Significantly improved the `rocsparse_sddmm` routine when using CSR format, especially as the number of columns in the dense `A` matrix (or rows in the dense `B` matrix) increases.
|
||||
* Improved the user documentation.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Fixed the `rmake.py` build script to properly handle `auto` and all options when selecting offload targets.
|
||||
* Fixed an issue when building rocSPARSE with the install script on some operating systems.
|
||||
* Fixed `std::fma` casting in host routines to properly deduce types. This could have previously caused compilation failures when building from source.
|
||||
|
||||
### **rocThrust** (4.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* `thrust::unique_ptr` - a smart pointer for managing device memory with automatic cleanup.
|
||||
* A new cmake option, `BUILD_OFFLOAD_COMPRESS`. When rocThrust is built with this option enabled, the `--offload-compress` switch is passed to the compiler. This causes the compiler to compress the binary that it generates. Compression can be useful when compiling for a large number of targets, because it often results in a larger binary. Without compression, in some cases, the generated binary may become so large symbols are placed out of range, resulting in linking errors. The new `BUILD_OFFLOAD_COMPRESS` option is set to `ON` by default.
|
||||
* Experimental SPIR-V support.
|
||||
|
||||
### **rocWMMA** (2.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Sample `perf_i8gemm` to demonstrate `int8_t` as matrix input data type.
|
||||
* Support for the gfx1150 target.
|
||||
|
||||
#### Changed
|
||||
|
||||
* Removed unnecessary const keyword to avoid compiler warnings.
|
||||
* rocWMMA has been moved into the new rocm-libraries "monorepo" repository {fab}`github` [rocm-libraries](https://github.com/ROCm/rocm-libraries). This repository consolidates a number of separate ROCm libraries and shared components.
|
||||
* The repository migration requires a few changes to the CMake configuration of rocWMMA.
|
||||
* The repository migration required the GTest dependency to be updated to v1.16.0.
|
||||
|
||||
#### Resolved issues
|
||||
|
||||
* Skip invalid test configurations when using 'register file' LDS mapping.
|
||||
* Ensured transform functions in samples are only available on the device.
|
||||
|
||||
### **RPP** (2.2.0)
|
||||
|
||||
#### Added
|
||||
|
||||
* Pinned buffer API support for HOST and HIP.
|
||||
|
||||
#### Changed
|
||||
|
||||
* AMDClag++ compiler has moved to `${ROCM_PATH}/lib/llvm/bin`.
|
||||
|
||||
#### Removed
|
||||
|
||||
* The `copy_param_float()` and `copy_param_uint()` mem copy helper functions have been removed as buffers now consistently use pinned/HIP memory.
|
||||
|
||||
#### Resolved issues
|
||||
* Test Suite - Error Code Capture updates.
|
||||
|
||||
## ROCm 7.1.1
|
||||
|
||||
See the [ROCm 7.1.1 release notes](https://rocm.docs.amd.com/en/docs-7.1.1/about/release-notes.html#rocm-7-1-1-release-notes)
|
||||
|
||||
1278
RELEASE.md
1278
RELEASE.md
File diff suppressed because it is too large
Load Diff
@@ -1,136 +1,136 @@
|
||||
ROCm Version,7.2.0,7.1.1,7.1.0,7.0.2,7.0.1/7.0.0,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0, 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>` [#os-compatibility-past-60]_,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,"Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04",Ubuntu 24.04,,,,,,
|
||||
,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,"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","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 10.1, 10.0, 9.7, 9.6, 9.4","RHEL 10.1, 10.0, 9.7, 9.6, 9.4","RHEL 10.0, 9.6, 9.4","RHEL 10.0, 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.6, 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.3, 9.2","RHEL 9.3, 9.2"
|
||||
,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,"RHEL 8.10, 8.9","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 SP7,SLES 15 SP7,SLES 15 SP7,SLES 15 SP7,SLES 15 SP7,"SLES 15 SP7, SP6","SLES 15 SP7, SP6",SLES 15 SP6,SLES 15 SP6,"SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","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 10, 9, 8","Oracle Linux 10, 9, 8","Oracle Linux 10, 9, 8","Oracle Linux 10, 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8",Oracle Linux 8.10,Oracle Linux 8.10,Oracle Linux 8.10,Oracle Linux 8.10,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,,,
|
||||
,"Debian 13, 12","Debian 13, 12","Debian 13, 12","Debian 13, 12",Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,,,,,,,,,,,
|
||||
,,,,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,,,,,,,,,,,,
|
||||
,Rocky Linux 9,Rocky Linux 9,Rocky Linux 9,Rocky Linux 9,Rocky Linux 9,,,,,,,,,,,,,,,,,,
|
||||
,.. _architecture-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA4,CDNA4,CDNA4,CDNA4,CDNA4,,,,,,,,,,,,,,,,,,
|
||||
,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3
|
||||
,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2
|
||||
,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA
|
||||
,RDNA4,RDNA4,RDNA4,RDNA4,RDNA4,RDNA4,RDNA4,RDNA4,,,,,,,,,,,,,,,
|
||||
,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3
|
||||
,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,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>` [#gpu-compatibility-past-60]_,gfx950,gfx950,gfx950,gfx950,gfx950,,,,,,,,,,,,,,,,,,
|
||||
,gfx1201,gfx1201,gfx1201,gfx1201,gfx1201,gfx1201,gfx1201,gfx1201,,,,,,,,,,,,,,,
|
||||
,gfx1200,gfx1200,gfx1200,gfx1200,gfx1200,gfx1200,gfx1200,gfx1200,,,,,,,,,,,,,,,
|
||||
,gfx1101,gfx1101,gfx1101,gfx1101,gfx1101,gfx1101,gfx1101,gfx1101,,,,,,,,,,,,,,,
|
||||
,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100
|
||||
,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030
|
||||
,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942, gfx942, gfx942, gfx942, gfx942, gfx942, gfx942
|
||||
,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a
|
||||
,gfx908,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>`,"2.9.1, 2.8.0, 2.7.1","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:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`,"2.20.0, 2.19.1, 2.18.1","2.20.0, 2.19.1, 2.18.1","2.20.0, 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>`,0.8.0,0.7.1,0.7.1,0.6.0,0.6.0,0.4.35,0.4.35,0.4.35,0.4.35,0.4.31,0.4.31,0.4.31,0.4.31,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26,0.4.26
|
||||
:doc:`verl <../compatibility/ml-compatibility/verl-compatibility>` [#verl_compat-past-60]_,N/A,N/A,N/A,N/A,0.6.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.3.0.post0,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>` [#stanford-megatron-lm_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,85f95ae,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat-past-60]_,N/A,N/A,N/A,N/A,2.4.0,2.4.0,N/A,N/A,2.4.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>` [#megablocks_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.7.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Ray <../compatibility/ml-compatibility/ray-compatibility>` [#ray_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,2.48.0.post0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>` [#llama-cpp_compat-past-60]_,N/A,N/A,N/A,N/A,b6652,b6356,b6356,b6356,b5997,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`FlashInfer <../compatibility/ml-compatibility/flashinfer-compatibility>` [#flashinfer_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,v0.2.5,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
`ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.23.2,1.23.1,1.22.0,1.22.0,1.22.0,1.20.0,1.20.0,1.20.0,1.20.0,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
`UCC <https://github.com/ROCm/ucc>`_,>=1.4.0,>=1.4.0,>=1.4.0,>=1.4.0,>=1.4.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=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>`_,>=1.17.0,>=1.17.0,>=1.17.0,>=1.17.0,>=1.17.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=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,2.8.5,2.8.5,2.8.5,2.6.0,2.6.0,2.5.0,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
|
||||
CUB,2.8.5,2.8.5,2.8.5,2.6.0,2.6.0,2.5.0,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
DRIVER & USER SPACE [#kfd_support-past-60]_,.. _kfd-userspace-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.30.0, 30.20.1, 30.20.0 [#mi325x_KVM-past-60]_, 30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x","30.20.1, 30.20.0 [#mi325x_KVM-past-60]_, 30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x","30.20.0 [#mi325x_KVM-past-60]_, 30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x","30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x","30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x, 6.2.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x"
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
ML & COMPUTER VISION,.. _mllibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`Composable Kernel <composable_kernel:index>`,1.2.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0
|
||||
:doc:`MIGraphX <amdmigraphx:index>`,2.15.0,2.14.0,2.14.0,2.13.0,2.13.0,2.12.0,2.12.0,2.12.0,2.12.0,2.11.0,2.11.0,2.11.0,2.11.0,2.10.0,2.10.0,2.10.0,2.10.0,2.9.0,2.9.0,2.9.0,2.9.0,2.8.0,2.8.0
|
||||
:doc:`MIOpen <miopen:index>`,3.5.1,3.5.1,3.5.1,3.5.0,3.5.0,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
|
||||
:doc:`MIVisionX <mivisionx:index>`,3.5.0,3.4.0,3.4.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0
|
||||
:doc:`rocAL <rocal:index>`,2.5.0,2.4.0,2.4.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0,2.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
|
||||
:doc:`rocDecode <rocdecode:index>`,1.5.0,1.4.0,1.4.0,1.0.0,1.0.0,0.10.0,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,N/A,N/A
|
||||
:doc:`rocJPEG <rocjpeg:index>`,1.3.0,1.2.0,1.2.0,1.1.0,1.1.0,0.8.0,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`rocPyDecode <rocpydecode:index>`,0.8.0,0.7.0,0.7.0,0.6.0,0.6.0,0.3.1,0.3.1,0.3.1,0.3.1,0.2.0,0.2.0,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`RPP <rpp:index>`,2.2.0,2.1.0,2.1.0,2.0.0,2.0.0,1.9.10,1.9.10,1.9.10,1.9.10,1.9.1,1.9.1,1.9.1,1.9.1,1.8.0,1.8.0,1.8.0,1.8.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
COMMUNICATION,.. _commlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`RCCL <rccl:index>`,2.27.7,2.27.7,2.27.7,2.26.6,2.26.6,2.22.3,2.22.3,2.22.3,2.22.3,2.21.5,2.21.5,2.21.5,2.21.5,2.20.5,2.20.5,2.20.5,2.20.5,2.18.6,2.18.6,2.18.6,2.18.6,2.18.3,2.18.3
|
||||
:doc:`rocSHMEM <rocshmem:index>`,3.2.0,3.1.0,3.0.0,3.0.0,3.0.0,2.0.1,2.0.1,2.0.0,2.0.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
MATH LIBS,.. _mathlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
`half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0
|
||||
:doc:`hipBLAS <hipblas:index>`,3.2.0,3.1.0,3.1.0,3.0.2,3.0.0,2.4.0,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0
|
||||
:doc:`hipBLASLt <hipblaslt:index>`,1.2.1,1.1.0,1.1.0,1.0.0,1.0.0,0.12.1,0.12.1,0.12.1,0.12.0,0.10.0,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.7.0,0.7.0,0.7.0,0.7.0,0.6.0,0.6.0
|
||||
:doc:`hipFFT <hipfft:index>`,1.0.22,1.0.21,1.0.21,1.0.20,1.0.20,1.0.18,1.0.18,1.0.18,1.0.18,1.0.17,1.0.17,1.0.17,1.0.17,1.0.16,1.0.15,1.0.15,1.0.14,1.0.14,1.0.14,1.0.14,1.0.14,1.0.13,1.0.13
|
||||
:doc:`hipfort <hipfort:index>`,0.7.1,0.7.1,0.7.1,0.7.0,0.7.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.1,0.5.1,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0
|
||||
:doc:`hipRAND <hiprand:index>`,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0,2.12.0,2.12.0,2.12.0,2.12.0,2.11.1,2.11.1,2.11.1,2.11.0,2.11.1,2.11.0,2.11.0,2.11.0,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16
|
||||
:doc:`hipSOLVER <hipsolver:index>`,3.2.0,3.1.0,3.1.0,3.0.0,3.0.0,2.4.0,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.1,2.1.1,2.1.1,2.1.0,2.0.0,2.0.0
|
||||
:doc:`hipSPARSE <hipsparse:index>`,4.2.0,4.1.0,4.1.0,4.0.1,4.0.1,3.2.0,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.1.1,3.1.1,3.1.1,3.1.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
|
||||
:doc:`hipSPARSELt <hipsparselt:index>`,0.2.6,0.2.5,0.2.5,0.2.4,0.2.4,0.2.3,0.2.3,0.2.3,0.2.3,0.2.2,0.2.2,0.2.2,0.2.2,0.2.1,0.2.1,0.2.1,0.2.1,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0
|
||||
:doc:`rocALUTION <rocalution:index>`,4.1.0,4.0.1,4.0.1,4.0.0,4.0.0,3.2.3,3.2.3,3.2.3,3.2.2,3.2.1,3.2.1,3.2.1,3.2.1,3.2.1,3.2.0,3.2.0,3.2.0,3.1.1,3.1.1,3.1.1,3.1.1,3.0.3,3.0.3
|
||||
:doc:`rocBLAS <rocblas:index>`,5.2.0,5.1.1,5.1.0,5.0.2,5.0.0,4.4.1,4.4.1,4.4.0,4.4.0,4.3.0,4.3.0,4.3.0,4.3.0,4.2.4,4.2.1,4.2.1,4.2.0,4.1.2,4.1.2,4.1.0,4.1.0,4.0.0,4.0.0
|
||||
:doc:`rocFFT <rocfft:index>`,1.0.36,1.0.35,1.0.35,1.0.34,1.0.34,1.0.32,1.0.32,1.0.32,1.0.32,1.0.31,1.0.31,1.0.31,1.0.31,1.0.30,1.0.29,1.0.29,1.0.28,1.0.27,1.0.27,1.0.27,1.0.26,1.0.25,1.0.23
|
||||
:doc:`rocRAND <rocrand:index>`,4.2.0,4.1.0,4.1.0,4.0.0,4.0.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.1,3.1.0,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,2.10.17
|
||||
:doc:`rocSOLVER <rocsolver:index>`,3.32.0,3.31.0,3.31.0,3.30.1,3.30.0,3.28.2,3.28.2,3.28.0,3.28.0,3.27.0,3.27.0,3.27.0,3.27.0,3.26.2,3.26.0,3.26.0,3.26.0,3.25.0,3.25.0,3.25.0,3.25.0,3.24.0,3.24.0
|
||||
:doc:`rocSPARSE <rocsparse:index>`,4.2.0,4.1.0,4.1.0,4.0.2,4.0.2,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.0.2,3.0.2
|
||||
:doc:`rocWMMA <rocwmma:index>`,2.2.0,2.1.0,2.0.0,2.0.0,2.0.0,1.7.0,1.7.0,1.7.0,1.7.0,1.6.0,1.6.0,1.6.0,1.6.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0
|
||||
:doc:`Tensile <tensile:src/index>`,4.44.0,4.44.0,4.44.0,4.44.0,4.44.0,4.43.0,4.43.0,4.43.0,4.43.0,4.42.0,4.42.0,4.42.0,4.42.0,4.41.0,4.41.0,4.41.0,4.41.0,4.40.0,4.40.0,4.40.0,4.40.0,4.39.0,4.39.0
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
PRIMITIVES,.. _primitivelibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`hipCUB <hipcub:index>`,4.2.0,4.1.0,4.1.0,4.0.0,4.0.0,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
|
||||
:doc:`hipTensor <hiptensor:index>`,2.2.0,2.0.0,2.0.0,2.0.0,2.0.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0,1.3.0,1.3.0,1.2.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0
|
||||
:doc:`rocPRIM <rocprim:index>`,4.2.0,4.1.0,4.1.0,4.0.1,4.0.0,3.4.1,3.4.1,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.2,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
|
||||
:doc:`rocThrust <rocthrust:index>`,4.2.0,4.1.0,4.1.0,4.0.0,4.0.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.1.1,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
SUPPORT LIBS,,,,,,,,,,,,,,,,,,,,,,,
|
||||
`hipother <https://github.com/ROCm/hipother>`_,7.2.26015,7.1.52802,7.1.25424,7.0.51831,7.0.51830,6.4.43483,6.4.43483,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
|
||||
`rocm-core <https://github.com/ROCm/rocm-core>`_,7.2.0,7.1.1,7.1.0,7.0.2,7.0.1/7.0.0,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0,6.1.5,6.1.2,6.1.1,6.1.0,6.0.2,6.0.0
|
||||
`ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,20240607.5.7,20240607.5.7,20240607.4.05,20240607.1.4246,20240125.5.08,20240125.5.08,20240125.5.08,20240125.3.30,20231016.2.245,20231016.2.245
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`AMD SMI <amdsmi:index>`,26.2.1,26.2.0,26.1.0,26.0.2,26.0.0,25.5.1,25.5.1,25.4.2,25.3.0,24.7.1,24.7.1,24.7.1,24.7.1,24.6.3,24.6.3,24.6.3,24.6.2,24.5.1,24.5.1,24.5.1,24.4.1,23.4.2,23.4.2
|
||||
:doc:`ROCm Data Center Tool <rdc:index>`,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0
|
||||
:doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
|
||||
:doc:`ROCm SMI <rocm_smi_lib:index>`,7.8.0,7.8.0,7.8.0,7.8.0,7.8.0,7.7.0,7.5.0,7.5.0,7.5.0,7.4.0,7.4.0,7.4.0,7.4.0,7.3.0,7.3.0,7.3.0,7.3.0,7.2.0,7.2.0,7.0.0,7.0.0,6.0.2,6.0.0
|
||||
:doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,1.3.0,1.3.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.0.60204,1.0.60202,1.0.60201,1.0.60200,1.0.60105,1.0.60102,1.0.60101,1.0.60100,1.0.60002,1.0.60000
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
PERFORMANCE TOOLS,,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,2.6.0,2.6.0,2.6.0,2.6.0,2.6.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0
|
||||
:doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.4.0,3.3.1,3.3.0,3.2.3,3.2.3,3.1.1,3.1.1,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.0.1,2.0.1,2.0.1,2.0.1,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.3.0,1.2.1,1.2.0,1.1.1,1.1.0,1.0.2,1.0.2,1.0.1,1.0.0,0.1.2,0.1.1,0.1.0,0.1.0,1.11.2,1.11.2,1.11.2,1.11.2,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`ROCProfiler <rocprofiler:index>`,2.0.70200,2.0.70101,2.0.70100,2.0.70002,2.0.70000,2.0.60403,2.0.60402,2.0.60401,2.0.60400,2.0.60303,2.0.60302,2.0.60301,2.0.60300,2.0.60204,2.0.60202,2.0.60201,2.0.60200,2.0.60105,2.0.60102,2.0.60101,2.0.60100,2.0.60002,2.0.60000
|
||||
:doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,1.1.0,1.0.0,1.0.0,1.0.0,1.0.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`ROCTracer <roctracer:index>`,4.1.70200,4.1.70101,4.1.70100,4.1.70002,4.1.70000,4.1.60403,4.1.60402,4.1.60401,4.1.60400,4.1.60303,4.1.60302,4.1.60301,4.1.60300,4.1.60204,4.1.60202,4.1.60201,4.1.60200,4.1.60105,4.1.60102,4.1.60101,4.1.60100,4.1.60002,4.1.60000
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
DEVELOPMENT TOOLS,,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`HIPIFY <hipify:index>`,22.0.0,20.0.0,20.0.0,20.0.0,20.0.0,19.0.0,19.0.0,19.0.0,19.0.0,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
:doc:`ROCm CMake <rocmcmakebuildtools:index>`,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.13.0,0.13.0,0.13.0,0.13.0,0.12.0,0.12.0,0.12.0,0.12.0,0.11.0,0.11.0
|
||||
:doc:`ROCdbgapi <rocdbgapi:index>`,0.77.4,0.77.4,0.77.4,0.77.4,0.77.3,0.77.2,0.77.2,0.77.2,0.77.2,0.77.0,0.77.0,0.77.0,0.77.0,0.76.0,0.76.0,0.76.0,0.76.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0
|
||||
:doc:`ROCm Debugger (ROCgdb) <rocgdb:index>`,16.3.0,16.3.0,16.3.0,16.3.0,16.3.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,14.2.0,14.2.0,14.2.0,14.2.0,14.1.0,14.1.0,14.1.0,14.1.0,13.2.0,13.2.0
|
||||
`rocprofiler-register <https://github.com/ROCm/rocprofiler-register>`_,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.3.0,0.3.0,0.3.0,0.3.0,N/A,N/A
|
||||
:doc:`ROCr Debug Agent <rocr_debug_agent:index>`,2.1.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.4,2.0.4,2.0.4,2.0.4,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
COMPILERS,.. _compilers-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
`clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A,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,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0
|
||||
:doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
|
||||
`Flang <https://github.com/ROCm/flang>`_,22.0.0.26014,20.0.025444,20.0.025425,20.0.0.25385,20.0.0.25314,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
:doc:`llvm-project <llvm-project:index>`,22.0.0.26014,20.0.025444,20.0.025425,20.0.0.25385,20.0.0.25314,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
`OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,22.0.0.26014,20.0.025444,20.0.025425,20.0.0.25385,20.0.0.25314,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
,,,,,,,,,,,,,,,,,,,,,,,
|
||||
RUNTIMES,.. _runtime-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`AMD CLR <hip:understand/amd_clr>`,7.2.26015,7.1.52802,7.1.25424,7.0.51831,7.0.51830,6.4.43484,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
|
||||
:doc:`HIP <hip:index>`,7.2.26015,7.1.52802,7.1.25424,7.0.51831,7.0.51830,6.4.43484,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
|
||||
`OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0
|
||||
:doc:`ROCr Runtime <rocr-runtime:index>`,1.18.0,1.18.0,1.18.0,1.18.0,1.18.0,1.15.0,1.15.0,1.15.0,1.15.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.13.0,1.13.0,1.13.0,1.13.0,1.13.0,1.12.0,1.12.0
|
||||
ROCm Version,7.1.1,7.1.0,7.0.2,7.0.1/7.0.0,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0, 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>` [#os-compatibility-past-60]_,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,Ubuntu 24.04.2,"Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04","Ubuntu 24.04.1, 24.04",Ubuntu 24.04,,,,,,
|
||||
,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5,"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","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 10.1, 10.0, 9.7, 9.6, 9.4","RHEL 10.0, 9.6, 9.4","RHEL 10.0, 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.6, 9.4","RHEL 9.6, 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.5, 9.4","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.4, 9.3, 9.2","RHEL 9.3, 9.2","RHEL 9.3, 9.2"
|
||||
,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,RHEL 8.10,"RHEL 8.10, 8.9","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 SP7,SLES 15 SP7,SLES 15 SP7,SLES 15 SP7,"SLES 15 SP7, SP6","SLES 15 SP7, SP6",SLES 15 SP6,SLES 15 SP6,"SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","SLES 15 SP6, SP5","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 10, 9, 8","Oracle Linux 10, 9, 8","Oracle Linux 10, 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8","Oracle Linux 9, 8",Oracle Linux 8.10,Oracle Linux 8.10,Oracle Linux 8.10,Oracle Linux 8.10,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,Oracle Linux 8.9,,,
|
||||
,"Debian 13, 12","Debian 13, 12","Debian 13, 12",Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,Debian 12,,,,,,,,,,,
|
||||
,,,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,Azure Linux 3.0,,,,,,,,,,,,
|
||||
,Rocky Linux 9,Rocky Linux 9,Rocky Linux 9,Rocky Linux 9,,,,,,,,,,,,,,,,,,
|
||||
,.. _architecture-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`Architecture <rocm-install-on-linux:reference/system-requirements>`,CDNA4,CDNA4,CDNA4,CDNA4,,,,,,,,,,,,,,,,,,
|
||||
,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3,CDNA3
|
||||
,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2,CDNA2
|
||||
,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA,CDNA
|
||||
,RDNA4,RDNA4,RDNA4,RDNA4,RDNA4,RDNA4,RDNA4,,,,,,,,,,,,,,,
|
||||
,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3,RDNA3
|
||||
,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,RDNA2,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>` [#gpu-compatibility-past-60]_,gfx950,gfx950,gfx950,gfx950,,,,,,,,,,,,,,,,,,
|
||||
,gfx1201,gfx1201,gfx1201,gfx1201,gfx1201,gfx1201,gfx1201,,,,,,,,,,,,,,,
|
||||
,gfx1200,gfx1200,gfx1200,gfx1200,gfx1200,gfx1200,gfx1200,,,,,,,,,,,,,,,
|
||||
,gfx1101,gfx1101,gfx1101,gfx1101,gfx1101,gfx1101,gfx1101,,,,,,,,,,,,,,,
|
||||
,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100,gfx1100
|
||||
,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030,gfx1030
|
||||
,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942,gfx942, gfx942, gfx942, gfx942, gfx942, gfx942, gfx942
|
||||
,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a,gfx90a
|
||||
,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:`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,0.6.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.3.0.post0,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>` [#stanford-megatron-lm_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,85f95ae,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>` [#dgl_compat-past-60]_,N/A,N/A,N/A,2.4.0,2.4.0,N/A,N/A,2.4.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>` [#megablocks_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,0.7.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`Ray <../compatibility/ml-compatibility/ray-compatibility>` [#ray_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,2.48.0.post0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>` [#llama-cpp_compat-past-60]_,N/A,N/A,N/A,b6652,b6356,b6356,b6356,b5997,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`FlashInfer <../compatibility/ml-compatibility/flashinfer-compatibility>` [#flashinfer_compat-past-60]_,N/A,N/A,N/A,N/A,N/A,N/A,v0.2.5,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
`ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.23.1,1.22.0,1.22.0,1.22.0,1.20.0,1.20.0,1.20.0,1.20.0,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.17.3,1.14.1,1.14.1
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
`UCC <https://github.com/ROCm/ucc>`_,>=1.4.0,>=1.4.0,>=1.4.0,>=1.4.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=1.3.0,>=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>`_,>=1.17.0,>=1.17.0,>=1.17.0,>=1.17.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=1.15.0,>=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,2.8.5,2.8.5,2.6.0,2.6.0,2.5.0,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
|
||||
CUB,2.8.5,2.8.5,2.6.0,2.6.0,2.5.0,2.5.0,2.5.0,2.5.0,2.3.2,2.3.2,2.3.2,2.3.2,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.1,2.0.1
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
DRIVER & USER SPACE [#kfd_support-past-60]_,.. _kfd-userspace-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.20.1, 30.20.0 [#mi325x_KVM-past-60]_, 30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x","30.20.0 [#mi325x_KVM-past-60]_, 30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x","30.10.2, 30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x","30.10.1 [#driver_patch-past-60]_, 30.10, 6.4.x, 6.3.x, 6.2.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.4.x, 6.3.x, 6.2.x, 6.1.x, 6.0.x, 5.7.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x","6.2.x, 6.1.x, 6.0.x, 5.7.x, 5.6.x"
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
ML & COMPUTER VISION,.. _mllibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`Composable Kernel <composable_kernel:index>`,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0
|
||||
:doc:`MIGraphX <amdmigraphx:index>`,2.14.0,2.14.0,2.13.0,2.13.0,2.12.0,2.12.0,2.12.0,2.12.0,2.11.0,2.11.0,2.11.0,2.11.0,2.10.0,2.10.0,2.10.0,2.10.0,2.9.0,2.9.0,2.9.0,2.9.0,2.8.0,2.8.0
|
||||
:doc:`MIOpen <miopen:index>`,3.5.1,3.5.1,3.5.0,3.5.0,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
|
||||
:doc:`MIVisionX <mivisionx:index>`,3.4.0,3.4.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0,2.5.0
|
||||
:doc:`rocAL <rocal:index>`,2.4.0,2.4.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0,2.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
|
||||
:doc:`rocDecode <rocdecode:index>`,1.4.0,1.4.0,1.0.0,1.0.0,0.10.0,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,N/A,N/A
|
||||
:doc:`rocJPEG <rocjpeg:index>`,1.2.0,1.2.0,1.1.0,1.1.0,0.8.0,0.8.0,0.8.0,0.8.0,0.6.0,0.6.0,0.6.0,0.6.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`rocPyDecode <rocpydecode:index>`,0.7.0,0.7.0,0.6.0,0.6.0,0.3.1,0.3.1,0.3.1,0.3.1,0.2.0,0.2.0,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`RPP <rpp:index>`,2.1.0,2.1.0,2.0.0,2.0.0,1.9.10,1.9.10,1.9.10,1.9.10,1.9.1,1.9.1,1.9.1,1.9.1,1.8.0,1.8.0,1.8.0,1.8.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
COMMUNICATION,.. _commlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`RCCL <rccl:index>`,2.27.7,2.27.7,2.26.6,2.26.6,2.22.3,2.22.3,2.22.3,2.22.3,2.21.5,2.21.5,2.21.5,2.21.5,2.20.5,2.20.5,2.20.5,2.20.5,2.18.6,2.18.6,2.18.6,2.18.6,2.18.3,2.18.3
|
||||
:doc:`rocSHMEM <rocshmem:index>`,3.1.0,3.0.0,3.0.0,3.0.0,2.0.1,2.0.1,2.0.0,2.0.0,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
MATH LIBS,.. _mathlibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
`half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0,1.12.0
|
||||
:doc:`hipBLAS <hipblas:index>`,3.1.0,3.1.0,3.0.2,3.0.0,2.4.0,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.0,2.1.0,2.1.0,2.1.0,2.0.0,2.0.0
|
||||
:doc:`hipBLASLt <hipblaslt:index>`,1.1.0,1.1.0,1.0.0,1.0.0,0.12.1,0.12.1,0.12.1,0.12.0,0.10.0,0.10.0,0.10.0,0.10.0,0.8.0,0.8.0,0.8.0,0.8.0,0.7.0,0.7.0,0.7.0,0.7.0,0.6.0,0.6.0
|
||||
:doc:`hipFFT <hipfft:index>`,1.0.21,1.0.21,1.0.20,1.0.20,1.0.18,1.0.18,1.0.18,1.0.18,1.0.17,1.0.17,1.0.17,1.0.17,1.0.16,1.0.15,1.0.15,1.0.14,1.0.14,1.0.14,1.0.14,1.0.14,1.0.13,1.0.13
|
||||
:doc:`hipfort <hipfort:index>`,0.7.1,0.7.1,0.7.0,0.7.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.1,0.5.1,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0
|
||||
:doc:`hipRAND <hiprand:index>`,3.1.0,3.1.0,3.0.0,3.0.0,2.12.0,2.12.0,2.12.0,2.12.0,2.11.1,2.11.1,2.11.1,2.11.0,2.11.1,2.11.0,2.11.0,2.11.0,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16,2.10.16
|
||||
:doc:`hipSOLVER <hipsolver:index>`,3.1.0,3.1.0,3.0.0,3.0.0,2.4.0,2.4.0,2.4.0,2.4.0,2.3.0,2.3.0,2.3.0,2.3.0,2.2.0,2.2.0,2.2.0,2.2.0,2.1.1,2.1.1,2.1.1,2.1.0,2.0.0,2.0.0
|
||||
:doc:`hipSPARSE <hipsparse:index>`,4.1.0,4.1.0,4.0.1,4.0.1,3.2.0,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.1.1,3.1.1,3.1.1,3.1.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
|
||||
:doc:`hipSPARSELt <hipsparselt:index>`,0.2.5,0.2.5,0.2.4,0.2.4,0.2.3,0.2.3,0.2.3,0.2.3,0.2.2,0.2.2,0.2.2,0.2.2,0.2.1,0.2.1,0.2.1,0.2.1,0.2.0,0.2.0,0.1.0,0.1.0,0.1.0,0.1.0
|
||||
:doc:`rocALUTION <rocalution:index>`,4.0.1,4.0.1,4.0.0,4.0.0,3.2.3,3.2.3,3.2.3,3.2.2,3.2.1,3.2.1,3.2.1,3.2.1,3.2.1,3.2.0,3.2.0,3.2.0,3.1.1,3.1.1,3.1.1,3.1.1,3.0.3,3.0.3
|
||||
:doc:`rocBLAS <rocblas:index>`,5.1.1,5.1.0,5.0.2,5.0.0,4.4.1,4.4.1,4.4.0,4.4.0,4.3.0,4.3.0,4.3.0,4.3.0,4.2.4,4.2.1,4.2.1,4.2.0,4.1.2,4.1.2,4.1.0,4.1.0,4.0.0,4.0.0
|
||||
:doc:`rocFFT <rocfft:index>`,1.0.35,1.0.35,1.0.34,1.0.34,1.0.32,1.0.32,1.0.32,1.0.32,1.0.31,1.0.31,1.0.31,1.0.31,1.0.30,1.0.29,1.0.29,1.0.28,1.0.27,1.0.27,1.0.27,1.0.26,1.0.25,1.0.23
|
||||
:doc:`rocRAND <rocrand:index>`,4.1.0,4.1.0,4.0.0,4.0.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.0,3.2.0,3.2.0,3.2.0,3.1.1,3.1.0,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,2.10.17
|
||||
:doc:`rocSOLVER <rocsolver:index>`,3.31.0,3.31.0,3.30.1,3.30.0,3.28.2,3.28.2,3.28.0,3.28.0,3.27.0,3.27.0,3.27.0,3.27.0,3.26.2,3.26.0,3.26.0,3.26.0,3.25.0,3.25.0,3.25.0,3.25.0,3.24.0,3.24.0
|
||||
:doc:`rocSPARSE <rocsparse:index>`,4.1.0,4.1.0,4.0.2,4.0.2,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.2,3.1.2,3.1.2,3.1.2,3.0.2,3.0.2
|
||||
:doc:`rocWMMA <rocwmma:index>`,2.1.0,2.0.0,2.0.0,2.0.0,1.7.0,1.7.0,1.7.0,1.7.0,1.6.0,1.6.0,1.6.0,1.6.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0
|
||||
:doc:`Tensile <tensile:src/index>`,4.44.0,4.44.0,4.44.0,4.44.0,4.43.0,4.43.0,4.43.0,4.43.0,4.42.0,4.42.0,4.42.0,4.42.0,4.41.0,4.41.0,4.41.0,4.41.0,4.40.0,4.40.0,4.40.0,4.40.0,4.39.0,4.39.0
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
PRIMITIVES,.. _primitivelibs-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`hipCUB <hipcub:index>`,4.1.0,4.1.0,4.0.0,4.0.0,3.4.0,3.4.0,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.1,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
|
||||
:doc:`hipTensor <hiptensor:index>`,2.0.0,2.0.0,2.0.0,2.0.0,1.5.0,1.5.0,1.5.0,1.5.0,1.4.0,1.4.0,1.4.0,1.4.0,1.3.0,1.3.0,1.3.0,1.3.0,1.2.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0
|
||||
:doc:`rocPRIM <rocprim:index>`,4.1.0,4.1.0,4.0.1,4.0.0,3.4.1,3.4.1,3.4.0,3.4.0,3.3.0,3.3.0,3.3.0,3.3.0,3.2.2,3.2.0,3.2.0,3.2.0,3.1.0,3.1.0,3.1.0,3.1.0,3.0.0,3.0.0
|
||||
:doc:`rocThrust <rocthrust:index>`,4.1.0,4.1.0,4.0.0,4.0.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.3.0,3.1.1,3.1.0,3.1.0,3.0.1,3.0.1,3.0.1,3.0.1,3.0.1,3.0.0,3.0.0
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
SUPPORT LIBS,,,,,,,,,,,,,,,,,,,,,,
|
||||
`hipother <https://github.com/ROCm/hipother>`_,7.1.52802,7.1.25424,7.0.51831,7.0.51830,6.4.43483,6.4.43483,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
|
||||
`rocm-core <https://github.com/ROCm/rocm-core>`_,7.1.1,7.1.0,7.0.2,7.0.1/7.0.0,6.4.3,6.4.2,6.4.1,6.4.0,6.3.3,6.3.2,6.3.1,6.3.0,6.2.4,6.2.2,6.2.1,6.2.0,6.1.5,6.1.2,6.1.1,6.1.0,6.0.2,6.0.0
|
||||
`ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,N/A [#ROCT-rocr-past-60]_,20240607.5.7,20240607.5.7,20240607.4.05,20240607.1.4246,20240125.5.08,20240125.5.08,20240125.5.08,20240125.3.30,20231016.2.245,20231016.2.245
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`AMD SMI <amdsmi:index>`,26.2.0,26.1.0,26.0.2,26.0.0,25.5.1,25.5.1,25.4.2,25.3.0,24.7.1,24.7.1,24.7.1,24.7.1,24.6.3,24.6.3,24.6.3,24.6.2,24.5.1,24.5.1,24.5.1,24.4.1,23.4.2,23.4.2
|
||||
:doc:`ROCm Data Center Tool <rdc:index>`,1.2.0,1.2.0,1.1.0,1.1.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0,0.3.0
|
||||
:doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
|
||||
:doc:`ROCm SMI <rocm_smi_lib:index>`,7.8.0,7.8.0,7.8.0,7.8.0,7.7.0,7.5.0,7.5.0,7.5.0,7.4.0,7.4.0,7.4.0,7.4.0,7.3.0,7.3.0,7.3.0,7.3.0,7.2.0,7.2.0,7.0.0,7.0.0,6.0.2,6.0.0
|
||||
:doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,1.3.0,1.2.0,1.2.0,1.2.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.1.0,1.0.60204,1.0.60202,1.0.60201,1.0.60200,1.0.60105,1.0.60102,1.0.60101,1.0.60100,1.0.60002,1.0.60000
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
PERFORMANCE TOOLS,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,2.6.0,2.6.0,2.6.0,2.6.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0,1.4.0
|
||||
:doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.3.1,3.3.0,3.2.3,3.2.3,3.1.1,3.1.1,3.1.0,3.1.0,3.0.0,3.0.0,3.0.0,3.0.0,2.0.1,2.0.1,2.0.1,2.0.1,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.2.1,1.2.0,1.1.1,1.1.0,1.0.2,1.0.2,1.0.1,1.0.0,0.1.2,0.1.1,0.1.0,0.1.0,1.11.2,1.11.2,1.11.2,1.11.2,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`ROCProfiler <rocprofiler:index>`,2.0.70101,2.0.70100,2.0.70002,2.0.70000,2.0.60403,2.0.60402,2.0.60401,2.0.60400,2.0.60303,2.0.60302,2.0.60301,2.0.60300,2.0.60204,2.0.60202,2.0.60201,2.0.60200,2.0.60105,2.0.60102,2.0.60101,2.0.60100,2.0.60002,2.0.60000
|
||||
:doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,1.0.0,1.0.0,1.0.0,1.0.0,0.6.0,0.6.0,0.6.0,0.6.0,0.5.0,0.5.0,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,N/A,N/A,N/A,N/A,N/A,N/A
|
||||
:doc:`ROCTracer <roctracer:index>`,4.1.70101,4.1.70100,4.1.70002,4.1.70000,4.1.60403,4.1.60402,4.1.60401,4.1.60400,4.1.60303,4.1.60302,4.1.60301,4.1.60300,4.1.60204,4.1.60202,4.1.60201,4.1.60200,4.1.60105,4.1.60102,4.1.60101,4.1.60100,4.1.60002,4.1.60000
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
DEVELOPMENT TOOLS,,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`HIPIFY <hipify:index>`,20.0.0,20.0.0,20.0.0,20.0.0,19.0.0,19.0.0,19.0.0,19.0.0,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
:doc:`ROCm CMake <rocmcmakebuildtools:index>`,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.14.0,0.13.0,0.13.0,0.13.0,0.13.0,0.12.0,0.12.0,0.12.0,0.12.0,0.11.0,0.11.0
|
||||
:doc:`ROCdbgapi <rocdbgapi:index>`,0.77.4,0.77.4,0.77.4,0.77.3,0.77.2,0.77.2,0.77.2,0.77.2,0.77.0,0.77.0,0.77.0,0.77.0,0.76.0,0.76.0,0.76.0,0.76.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0,0.71.0
|
||||
:doc:`ROCm Debugger (ROCgdb) <rocgdb:index>`,16.3.0,16.3.0,16.3.0,16.3.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,15.2.0,14.2.0,14.2.0,14.2.0,14.2.0,14.1.0,14.1.0,14.1.0,14.1.0,13.2.0,13.2.0
|
||||
`rocprofiler-register <https://github.com/ROCm/rocprofiler-register>`_,0.5.0,0.5.0,0.5.0,0.5.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.4.0,0.3.0,0.3.0,0.3.0,0.3.0,N/A,N/A
|
||||
:doc:`ROCr Debug Agent <rocr_debug_agent:index>`,2.1.0,2.1.0,2.1.0,2.1.0,2.0.4,2.0.4,2.0.4,2.0.4,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3,2.0.3
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
COMPILERS,.. _compilers-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
`clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A,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,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0,0.5.0
|
||||
:doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.1.1,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0,1.0.0
|
||||
`Flang <https://github.com/ROCm/flang>`_,20.0.025444,20.0.025425,20.0.0.25385,20.0.0.25314,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24455,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
:doc:`llvm-project <llvm-project:index>`,20.0.025444,20.0.025425,20.0.0.25385,20.0.0.25314,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
`OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,20.0.025444,20.0.025425,20.0.0.25385,20.0.0.25314,19.0.0.25224,19.0.0.25224,19.0.0.25184,19.0.0.25133,18.0.0.25012,18.0.0.25012,18.0.0.24491,18.0.0.24491,18.0.0.24392,18.0.0.24355,18.0.0.24355,18.0.0.24232,17.0.0.24193,17.0.0.24193,17.0.0.24154,17.0.0.24103,17.0.0.24012,17.0.0.23483
|
||||
,,,,,,,,,,,,,,,,,,,,,,
|
||||
RUNTIMES,.. _runtime-support-compatibility-matrix-past-60:,,,,,,,,,,,,,,,,,,,,,
|
||||
:doc:`AMD CLR <hip:understand/amd_clr>`,7.1.52802,7.1.25424,7.0.51831,7.0.51830,6.4.43484,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
|
||||
:doc:`HIP <hip:index>`,7.1.52802,7.1.25424,7.0.51831,7.0.51830,6.4.43484,6.4.43484,6.4.43483,6.4.43482,6.3.42134,6.3.42134,6.3.42133,6.3.42131,6.2.41134,6.2.41134,6.2.41134,6.2.41133,6.1.40093,6.1.40093,6.1.40092,6.1.40091,6.1.32831,6.1.32830
|
||||
`OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0,2.0.0
|
||||
:doc:`ROCr Runtime <rocr-runtime:index>`,1.18.0,1.18.0,1.18.0,1.18.0,1.15.0,1.15.0,1.15.0,1.15.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.14.0,1.13.0,1.13.0,1.13.0,1.13.0,1.13.0,1.12.0,1.12.0
|
||||
|
||||
|
@@ -22,12 +22,12 @@ compatibility and system requirements.
|
||||
.. container:: format-big-table
|
||||
|
||||
.. csv-table::
|
||||
:header: "ROCm Version", "7.2.0", "7.1.1", "6.4.0"
|
||||
:header: "ROCm Version", "7.1.1", "7.1.0", "6.4.0"
|
||||
:stub-columns: 1
|
||||
|
||||
:ref:`Operating systems & kernels <OS-kernel-versions>` [#os-compatibility]_,Ubuntu 24.04.3,Ubuntu 24.04.3,Ubuntu 24.04.2
|
||||
,Ubuntu 22.04.5,Ubuntu 22.04.5,Ubuntu 22.04.5
|
||||
,"RHEL 10.1, 10.0, 9.7, 9.6, 9.4","RHEL 10.1, 10.0, 9.7, 9.6, 9.4","RHEL 9.5, 9.4"
|
||||
,"RHEL 10.1, 10.0, 9.7, |br| 9.6, 9.4","RHEL 10.0, 9.6, 9.4","RHEL 9.5, 9.4"
|
||||
,RHEL 8.10,RHEL 8.10,RHEL 8.10
|
||||
,SLES 15 SP7,SLES 15 SP7,SLES 15 SP6
|
||||
,"Oracle Linux 10, 9, 8","Oracle Linux 10, 9, 8","Oracle Linux 9, 8"
|
||||
@@ -43,7 +43,7 @@ compatibility and system requirements.
|
||||
,RDNA3,RDNA3,RDNA3
|
||||
,RDNA2,RDNA2,RDNA2
|
||||
,.. _gpu-support-compatibility-matrix:,,
|
||||
:doc:`GPU / LLVM target <rocm-install-on-linux:reference/system-requirements>` [#gpu-compatibility]_,gfx950,gfx950,
|
||||
:doc:`GPU / LLVM target <rocm-install-on-linux:reference/system-requirements>` [#gpu-compatibility]_,gfx950,gfx950,
|
||||
,gfx1201,gfx1201,
|
||||
,gfx1200,gfx1200,
|
||||
,gfx1101,gfx1101,
|
||||
@@ -54,12 +54,12 @@ compatibility and system requirements.
|
||||
,gfx908,gfx908,gfx908
|
||||
,,,
|
||||
FRAMEWORK SUPPORT,.. _framework-support-compatibility-matrix:,,
|
||||
:doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`,"2.9.1, 2.8.0, 2.7.1","2.9, 2.8, 2.7","2.6, 2.5, 2.4, 2.3"
|
||||
: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:`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>`,0.8.0,0.7.1,0.4.35
|
||||
: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
|
||||
:doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>` [#llama-cpp_compat]_,N/A,N/A,b5997
|
||||
`ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.23.2,1.23.1,1.20.0
|
||||
`ONNX Runtime <https://onnxruntime.ai/docs/build/eps.html#amd-migraphx>`_,1.23.1,1.22.0,1.20.0
|
||||
,,,
|
||||
THIRD PARTY COMMS,.. _thirdpartycomms-support-compatibility-matrix:,,
|
||||
`UCC <https://github.com/ROCm/ucc>`_,>=1.4.0,>=1.4.0,>=1.3.0
|
||||
@@ -70,70 +70,70 @@ compatibility and system requirements.
|
||||
CUB,2.8.5,2.8.5,2.5.0
|
||||
,,,
|
||||
DRIVER & USER SPACE [#kfd_support]_,.. _kfd-userspace-support-compatibility-matrix:,,
|
||||
:doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.30.0, 30.20.1, 30.20.0 [#mi325x_KVM]_, |br| 30.10.2, 30.10.1 [#driver_patch]_, |br| 30.10, 6.4.x","30.20.1, 30.20.0 [#mi325x_KVM]_, |br| 30.10.2, 30.10.1 [#driver_patch]_, |br| 30.10, 6.4.x","6.4.x, 6.3.x, 6.2.x, 6.1.x"
|
||||
:doc:`AMD GPU Driver <rocm-install-on-linux:reference/user-kernel-space-compat-matrix>`,"30.20.1, 30.20.0 [#mi325x_KVM]_, |br| 30.10.2, 30.10.1 [#driver_patch]_, |br| 30.10, 6.4.x","30.20.0 [#mi325x_KVM]_, 30.10.2, |br| 30.10.1 [#driver_patch]_, 30.10, 6.4.x","6.4.x, 6.3.x, 6.2.x, 6.1.x"
|
||||
,,,
|
||||
ML & COMPUTER VISION,.. _mllibs-support-compatibility-matrix:,,
|
||||
:doc:`Composable Kernel <composable_kernel:index>`,1.2.0,1.1.0,1.1.0
|
||||
:doc:`MIGraphX <amdmigraphx:index>`,2.15.0,2.14.0,2.12.0
|
||||
:doc:`Composable Kernel <composable_kernel:index>`,1.1.0,1.1.0,1.1.0
|
||||
:doc:`MIGraphX <amdmigraphx:index>`,2.14.0,2.14.0,2.12.0
|
||||
:doc:`MIOpen <miopen:index>`,3.5.1,3.5.1,3.4.0
|
||||
:doc:`MIVisionX <mivisionx:index>`,3.5.0,3.4.0,3.2.0
|
||||
:doc:`rocAL <rocal:index>`,2.5.0,2.4.0,2.2.0
|
||||
:doc:`rocDecode <rocdecode:index>`,1.5.0,1.4.0,0.10.0
|
||||
:doc:`rocJPEG <rocjpeg:index>`,1.3.0,1.2.0,0.8.0
|
||||
:doc:`rocPyDecode <rocpydecode:index>`,0.8.0,0.7.0,0.3.1
|
||||
:doc:`RPP <rpp:index>`,2.2.0,2.1.0,1.9.10
|
||||
:doc:`MIVisionX <mivisionx:index>`,3.4.0,3.4.0,3.2.0
|
||||
:doc:`rocAL <rocal:index>`,2.4.0,2.4.0,2.2.0
|
||||
:doc:`rocDecode <rocdecode:index>`,1.4.0,1.4.0,0.10.0
|
||||
:doc:`rocJPEG <rocjpeg:index>`,1.2.0,1.2.0,0.8.0
|
||||
:doc:`rocPyDecode <rocpydecode:index>`,0.7.0,0.7.0,0.3.1
|
||||
:doc:`RPP <rpp:index>`,2.1.0,2.1.0,1.9.10
|
||||
,,,
|
||||
COMMUNICATION,.. _commlibs-support-compatibility-matrix:,,
|
||||
:doc:`RCCL <rccl:index>`,2.27.7,2.27.7,2.22.3
|
||||
:doc:`rocSHMEM <rocshmem:index>`,3.2.0,3.1.0,2.0.0
|
||||
:doc:`rocSHMEM <rocshmem:index>`,3.1.0,3.0.0,2.0.0
|
||||
,,,
|
||||
MATH LIBS,.. _mathlibs-support-compatibility-matrix:,,
|
||||
`half <https://github.com/ROCm/half>`_ ,1.12.0,1.12.0,1.12.0
|
||||
:doc:`hipBLAS <hipblas:index>`,3.2.0,3.1.0,2.4.0
|
||||
:doc:`hipBLASLt <hipblaslt:index>`,1.2.1,1.1.0,0.12.0
|
||||
:doc:`hipFFT <hipfft:index>`,1.0.22,1.0.21,1.0.18
|
||||
:doc:`hipBLAS <hipblas:index>`,3.1.0,3.1.0,2.4.0
|
||||
:doc:`hipBLASLt <hipblaslt:index>`,1.1.0,1.1.0,0.12.0
|
||||
:doc:`hipFFT <hipfft:index>`,1.0.21,1.0.21,1.0.18
|
||||
:doc:`hipfort <hipfort:index>`,0.7.1,0.7.1,0.6.0
|
||||
:doc:`hipRAND <hiprand:index>`,3.1.0,3.1.0,2.12.0
|
||||
:doc:`hipSOLVER <hipsolver:index>`,3.2.0,3.1.0,2.4.0
|
||||
:doc:`hipSPARSE <hipsparse:index>`,4.2.0,4.1.0,3.2.0
|
||||
:doc:`hipSPARSELt <hipsparselt:index>`,0.2.6,0.2.5,0.2.3
|
||||
:doc:`rocALUTION <rocalution:index>`,4.1.0,4.0.1,3.2.2
|
||||
:doc:`rocBLAS <rocblas:index>`,5.2.0,5.1.1,4.4.0
|
||||
:doc:`rocFFT <rocfft:index>`,1.0.36,1.0.35,1.0.32
|
||||
:doc:`rocRAND <rocrand:index>`,4.2.0,4.1.0,3.3.0
|
||||
:doc:`rocSOLVER <rocsolver:index>`,3.32.0,3.31.0,3.28.0
|
||||
:doc:`rocSPARSE <rocsparse:index>`,4.2.0,4.1.0,3.4.0
|
||||
:doc:`rocWMMA <rocwmma:index>`,2.2.0,2.1.0,1.7.0
|
||||
:doc:`hipSOLVER <hipsolver:index>`,3.1.0,3.1.0,2.4.0
|
||||
:doc:`hipSPARSE <hipsparse:index>`,4.1.0,4.1.0,3.2.0
|
||||
:doc:`hipSPARSELt <hipsparselt:index>`,0.2.5,0.2.5,0.2.3
|
||||
:doc:`rocALUTION <rocalution:index>`,4.0.1,4.0.1,3.2.2
|
||||
:doc:`rocBLAS <rocblas:index>`,5.1.1,5.1.0,4.4.0
|
||||
:doc:`rocFFT <rocfft:index>`,1.0.35,1.0.35,1.0.32
|
||||
:doc:`rocRAND <rocrand:index>`,4.1.0,4.1.0,3.3.0
|
||||
:doc:`rocSOLVER <rocsolver:index>`,3.31.0,3.31.0,3.28.0
|
||||
:doc:`rocSPARSE <rocsparse:index>`,4.1.0,4.1.0,3.4.0
|
||||
:doc:`rocWMMA <rocwmma:index>`,2.1.0,2.0.0,1.7.0
|
||||
:doc:`Tensile <tensile:src/index>`,4.44.0,4.44.0,4.43.0
|
||||
,,,
|
||||
PRIMITIVES,.. _primitivelibs-support-compatibility-matrix:,,
|
||||
:doc:`hipCUB <hipcub:index>`,4.2.0,4.1.0,3.4.0
|
||||
:doc:`hipTensor <hiptensor:index>`,2.2.0,2.0.0,1.5.0
|
||||
:doc:`rocPRIM <rocprim:index>`,4.2.0,4.1.0,3.4.0
|
||||
:doc:`rocThrust <rocthrust:index>`,4.2.0,4.1.0,3.3.0
|
||||
:doc:`hipCUB <hipcub:index>`,4.1.0,4.1.0,3.4.0
|
||||
:doc:`hipTensor <hiptensor:index>`,2.0.0,2.0.0,1.5.0
|
||||
:doc:`rocPRIM <rocprim:index>`,4.1.0,4.1.0,3.4.0
|
||||
:doc:`rocThrust <rocthrust:index>`,4.1.0,4.1.0,3.3.0
|
||||
,,,
|
||||
SUPPORT LIBS,,,
|
||||
`hipother <https://github.com/ROCm/hipother>`_,7.2.26015,7.1.52802,6.4.43482
|
||||
`rocm-core <https://github.com/ROCm/rocm-core>`_,7.2.0,7.1.1,6.4.0
|
||||
`hipother <https://github.com/ROCm/hipother>`_,7.1.52802,7.1.25424,6.4.43482
|
||||
`rocm-core <https://github.com/ROCm/rocm-core>`_,7.1.1,7.1.0,6.4.0
|
||||
`ROCT-Thunk-Interface <https://github.com/ROCm/ROCT-Thunk-Interface>`_,N/A [#ROCT-rocr]_,N/A [#ROCT-rocr]_,N/A [#ROCT-rocr]_
|
||||
,,,
|
||||
SYSTEM MGMT TOOLS,.. _tools-support-compatibility-matrix:,,
|
||||
:doc:`AMD SMI <amdsmi:index>`,26.2.1,26.2.0,25.3.0
|
||||
:doc:`AMD SMI <amdsmi:index>`,26.2.0,26.1.0,25.3.0
|
||||
:doc:`ROCm Data Center Tool <rdc:index>`,1.2.0,1.2.0,0.3.0
|
||||
:doc:`rocminfo <rocminfo:index>`,1.0.0,1.0.0,1.0.0
|
||||
:doc:`ROCm SMI <rocm_smi_lib:index>`,7.8.0,7.8.0,7.5.0
|
||||
:doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,1.3.0,1.3.0,1.1.0
|
||||
:doc:`ROCm Validation Suite <rocmvalidationsuite:index>`,1.3.0,1.2.0,1.1.0
|
||||
,,,
|
||||
PERFORMANCE TOOLS,,,
|
||||
:doc:`ROCm Bandwidth Test <rocm_bandwidth_test:index>`,2.6.0,2.6.0,1.4.0
|
||||
:doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.4.0,3.3.1,3.1.0
|
||||
:doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.3.0,1.2.1,1.0.0
|
||||
:doc:`ROCProfiler <rocprofiler:index>`,2.0.70200,2.0.70101,2.0.60400
|
||||
:doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,1.1.0,1.0.0,0.6.0
|
||||
:doc:`ROCTracer <roctracer:index>`,4.1.70200,4.1.70101,4.1.60400
|
||||
:doc:`ROCm Compute Profiler <rocprofiler-compute:index>`,3.3.1,3.3.0,3.1.0
|
||||
:doc:`ROCm Systems Profiler <rocprofiler-systems:index>`,1.2.1,1.2.0,1.0.0
|
||||
:doc:`ROCProfiler <rocprofiler:index>`,2.0.70101,2.0.70100,2.0.60400
|
||||
:doc:`ROCprofiler-SDK <rocprofiler-sdk:index>`,1.0.0,1.0.0,0.6.0
|
||||
:doc:`ROCTracer <roctracer:index>`,4.1.70101,4.1.70100,4.1.60400
|
||||
,,,
|
||||
DEVELOPMENT TOOLS,,,
|
||||
:doc:`HIPIFY <hipify:index>`,22.0.0,20.0.0,19.0.0
|
||||
:doc:`HIPIFY <hipify:index>`,20.0.0,20.0.0,19.0.0
|
||||
:doc:`ROCm CMake <rocmcmakebuildtools:index>`,0.14.0,0.14.0,0.14.0
|
||||
:doc:`ROCdbgapi <rocdbgapi:index>`,0.77.4,0.77.4,0.77.2
|
||||
:doc:`ROCm Debugger (ROCgdb) <rocgdb:index>`,16.3.0,16.3.0,15.2.0
|
||||
@@ -143,21 +143,20 @@ compatibility and system requirements.
|
||||
COMPILERS,.. _compilers-support-compatibility-matrix:,,
|
||||
`clang-ocl <https://github.com/ROCm/clang-ocl>`_,N/A,N/A,N/A
|
||||
:doc:`hipCC <hipcc:index>`,1.1.1,1.1.1,1.1.1
|
||||
`Flang <https://github.com/ROCm/flang>`_,22.0.0.26014,20.0.025444,19.0.0.25133
|
||||
:doc:`llvm-project <llvm-project:index>`,22.0.0.26014,20.0.025444,19.0.0.25133
|
||||
`OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,22.0.0.26014,20.0.025444,19.0.0.25133
|
||||
`Flang <https://github.com/ROCm/flang>`_,20.0.025444,20.0.025425,19.0.0.25133
|
||||
:doc:`llvm-project <llvm-project:index>`,20.0.025444,20.0.025425,19.0.0.25133
|
||||
`OpenMP <https://github.com/ROCm/llvm-project/tree/amd-staging/openmp>`_,20.0.025444,20.0.025425,19.0.0.25133
|
||||
,,,
|
||||
RUNTIMES,.. _runtime-support-compatibility-matrix:,,
|
||||
:doc:`AMD CLR <hip:understand/amd_clr>`,7.2.26015,7.1.52802,6.4.43482
|
||||
:doc:`HIP <hip:index>`,7.2.26015,7.1.52802,6.4.43482
|
||||
:doc:`AMD CLR <hip:understand/amd_clr>`,7.1.52802,7.1.25424,6.4.43482
|
||||
:doc:`HIP <hip:index>`,7.1.52802,7.1.25424,6.4.43482
|
||||
`OpenCL Runtime <https://github.com/ROCm/clr/tree/develop/opencl>`_,2.0.0,2.0.0,2.0.0
|
||||
:doc:`ROCr Runtime <rocr-runtime:index>`,1.18.0,1.18.0,1.15.0
|
||||
|
||||
|
||||
.. rubric:: Footnotes
|
||||
|
||||
.. [#os-compatibility] Some operating systems are supported on specific GPUs. For detailed information about operating systems supported on ROCm 7.2.0, see the latest :ref:`supported_distributions`. For version specific information, see `ROCm 7.1.1 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.1/reference/system-requirements.html#supported-operating-systems>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-operating-systems>`__.
|
||||
.. [#gpu-compatibility] Some GPUs have limited operating system support. For detailed information about GPUs supporting ROCm 7.2.0, see the latest :ref:`supported_GPUs`. For version specific information, see `ROCm 7.1.1 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.1/reference/system-requirements.html#supported-gpus>`__, `ROCm 7.1.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.0/reference/system-requirements.html#supported-gpus>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-gpus>`__.
|
||||
.. [#os-compatibility] Some operating systems are supported on limited GPUs. For detailed information, see the latest :ref:`supported_distributions`. For version specific information, see `ROCm 7.1.1 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.1/reference/system-requirements.html#supported-operating-systems>`__, `ROCm 7.1.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.0/reference/system-requirements.html#supported-operating-systems>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-operating-systems>`__.
|
||||
.. [#gpu-compatibility] Some GPUs have limited operating system support. For detailed information, see the latest :ref:`supported_GPUs`. For version specific information, see `ROCm 7.1.1 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.1/reference/system-requirements.html#supported-gpus>`__, `ROCm 7.1.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.0/reference/system-requirements.html#supported-gpus>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-gpus>`__.
|
||||
.. [#dgl_compat] DGL is supported only on ROCm 7.0.0, ROCm 6.4.3 and ROCm 6.4.0.
|
||||
.. [#llama-cpp_compat] llama.cpp is supported only on ROCm 7.0.0 and ROCm 6.4.x.
|
||||
.. [#mi325x_KVM] For AMD Instinct MI325X KVM SR-IOV users, do not use AMD GPU Driver (amdgpu) 30.20.0.
|
||||
@@ -170,7 +169,8 @@ compatibility and system requirements.
|
||||
Operating systems, kernel and Glibc versions
|
||||
*********************************************
|
||||
|
||||
For detailed information on operating system supported on ROCm 7.2.0 and associated Kernel and Glibc version, see the latest :ref:`supported_distributions`. For version specific information, see `ROCm 7.1.1 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.1/reference/system-requirements.html#supported-operating-systems>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-operating-systems>`__.
|
||||
For detailed information on operating system supported on ROCm 7.1.1 and associated Kernel and Glibc version, see the latest :ref:`supported_distributions`. For version specific information, see `ROCm 7.1.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.0/reference/system-requirements.html#supported-operating-systems>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-operating-systems>`__.
|
||||
|
||||
.. note::
|
||||
|
||||
* See `Red Hat Enterprise Linux Release Dates <https://access.redhat.com/articles/3078>`_ to learn about the specific kernel versions supported on Red Hat Enterprise Linux (RHEL).
|
||||
@@ -201,10 +201,10 @@ Expand for full historical view of:
|
||||
|
||||
.. rubric:: Footnotes
|
||||
|
||||
.. [#os-compatibility-past-60] Some operating systems are supported on specific GPUs. For detailed information, see :ref:`supported_distributions` and select the required ROCm version for version specific support.
|
||||
.. [#gpu-compatibility-past-60] Some GPUs have limited operating system support. For detailed information, see :ref:`supported_GPUs` and select the required ROCm version for version specific support.
|
||||
.. [#os-compatibility-past-60] Some operating systems are supported on limited GPUs. For detailed information, see the latest :ref:`supported_distributions`. For version specific information, see `ROCm 7.1.1 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.1/reference/system-requirements.html#supported-operating-systems>`__, `ROCm 7.1.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.0/reference/system-requirements.html#supported-operating-systems>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-operating-systems>`__.
|
||||
.. [#gpu-compatibility-past-60] Some GPUs have limited operating system support. For detailed information, see the latest :ref:`supported_GPUs`. For version specific information, see `ROCm 7.1.1 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.1/reference/system-requirements.html#supported-gpus>`__, `ROCm 7.1.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-7.1.0/reference/system-requirements.html#supported-gpus>`__, and `ROCm 6.4.0 <https://rocm.docs.amd.com/projects/install-on-linux/en/docs-6.4.0/reference/system-requirements.html#supported-gpus>`__.
|
||||
.. [#tf-mi350-past-60] TensorFlow 2.17.1 is not supported on AMD Instinct MI350 Series GPUs. Use TensorFlow 2.19.1 or 2.18.1 with MI350 Series GPUs instead.
|
||||
.. [#verl_compat-past-60] verl is supported only on ROCm 6.2.0.
|
||||
.. [#verl_compat-past-60] verl is supported only on ROCm 7.0.0 and 6.2.0.
|
||||
.. [#stanford-megatron-lm_compat-past-60] Stanford Megatron-LM is supported only on ROCm 6.3.0.
|
||||
.. [#dgl_compat-past-60] DGL is supported only on ROCm 7.0.0, ROCm 6.4.3 and ROCm 6.4.0.
|
||||
.. [#megablocks_compat-past-60] Megablocks is supported only on ROCm 6.3.0.
|
||||
|
||||
@@ -36,9 +36,63 @@ Support overview
|
||||
- You can also consult the upstream `Installation guide <https://www.dgl.ai/pages/start.html>`__
|
||||
for additional context.
|
||||
|
||||
Version support
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
DGL is supported on `ROCm 7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__,
|
||||
`ROCm 6.4.3 <https://repo.radeon.com/rocm/apt/6.4.3/>`__, and `ROCm 6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__.
|
||||
|
||||
Supported devices
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
**Officially Supported**: AMD Instinct™ MI300X, MI250X
|
||||
|
||||
.. _dgl-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
DGL can be used for Graph Learning, and building popular graph models like
|
||||
GAT, GCN, and GraphSage. Using these models, a variety of use cases are supported:
|
||||
|
||||
- Recommender systems
|
||||
- Network Optimization and Analysis
|
||||
- 1D (Temporal) and 2D (Image) Classification
|
||||
- Drug Discovery
|
||||
|
||||
For use cases and recommendations, refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__,
|
||||
where you can search for DGL examples and best practices to optimize your workloads on AMD GPUs.
|
||||
|
||||
* Although multiple use cases of DGL have been tested and verified, a few have been
|
||||
outlined in the `DGL in the Real World: Running GNNs on Real Use Cases
|
||||
<https://rocm.blogs.amd.com/artificial-intelligence/dgl_blog2/README.html>`__ blog
|
||||
post, which walks through four real-world graph neural network (GNN) workloads
|
||||
implemented with the Deep Graph Library on ROCm. It covers tasks ranging from
|
||||
heterogeneous e-commerce graphs and multiplex networks (GATNE) to molecular graph
|
||||
regression (GNN-FiLM) and EEG-based neurological diagnosis (EEG-GCNN). For each use
|
||||
case, the authors detail: the dataset and task, how DGL is used, and their experience
|
||||
porting to ROCm. It is shown that DGL codebases often run without modification, with
|
||||
seamless integration of graph operations, message passing, sampling, and convolution.
|
||||
|
||||
* The `Graph Neural Networks (GNNs) at Scale: DGL with ROCm on AMD Hardware
|
||||
<https://rocm.blogs.amd.com/artificial-intelligence/why-graph-neural/README.html>`__
|
||||
blog post introduces the Deep Graph Library (DGL) and its enablement on the AMD ROCm platform,
|
||||
bringing high-performance graph neural network (GNN) training to AMD GPUs. DGL bridges
|
||||
the gap between dense tensor frameworks and the irregular nature of graph data through a
|
||||
graph-first, message-passing abstraction. Its design ensures scalability, flexibility, and
|
||||
interoperability across frameworks like PyTorch and TensorFlow. AMD’s ROCm integration
|
||||
enables DGL to run efficiently on HIP-based GPUs, supported by prebuilt Docker containers
|
||||
and open-source repositories. This marks a major step in AMD's mission to advance open,
|
||||
scalable AI ecosystems beyond traditional architectures.
|
||||
|
||||
You can pre-process datasets and begin training on AMD GPUs through:
|
||||
|
||||
* Single-GPU training/inference
|
||||
* Multi-GPU training
|
||||
|
||||
.. _dgl-docker-compat:
|
||||
|
||||
Compatibility matrix
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
@@ -60,7 +114,6 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- PyTorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
- GPU
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -71,7 +124,6 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.8.0 <https://github.com/pytorch/pytorch/releases/tag/v2.8.0>`__
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -82,7 +134,6 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.6.0 <https://github.com/pytorch/pytorch/releases/tag/v2.6.0>`__
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -93,7 +144,6 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.7.1 <https://github.com/pytorch/pytorch/releases/tag/v2.7.1>`__
|
||||
- 22.04
|
||||
- `3.10.16 <https://www.python.org/downloads/release/python-31016/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -104,7 +154,6 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.6.0 <https://github.com/pytorch/pytorch/releases/tag/v2.6.0>`__
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -115,7 +164,6 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.6.0 <https://github.com/pytorch/pytorch/releases/tag/v2.6.0>`__
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -126,7 +174,7 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.4.1 <https://github.com/pytorch/pytorch/releases/tag/v2.4.1>`__
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -137,7 +185,7 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.4.1 <https://github.com/pytorch/pytorch/releases/tag/v2.4.1>`__
|
||||
- 22.04
|
||||
- `3.10.16 <https://www.python.org/downloads/release/python-31016/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -148,10 +196,7 @@ Click the |docker-icon| to view the image on Docker Hub.
|
||||
- `2.3.0 <https://github.com/pytorch/pytorch/releases/tag/v2.3.0>`__
|
||||
- 22.04
|
||||
- `3.10.16 <https://www.python.org/downloads/release/python-31016/>`__
|
||||
- MI300X, MI250X
|
||||
|
||||
|
||||
.. _dgl-key-rocm-libraries:
|
||||
|
||||
|
||||
Key ROCm libraries for DGL
|
||||
================================================================================
|
||||
@@ -265,9 +310,8 @@ If you prefer to build it yourself, ensure the following dependencies are instal
|
||||
multiplication (GEMM) and accumulation operations with mixed precision
|
||||
support.
|
||||
|
||||
.. _dgl-supported-features-latest:
|
||||
|
||||
Supported features with ROCm 7.0.0
|
||||
Supported features
|
||||
================================================================================
|
||||
|
||||
Many functions and methods available upstream are also supported in DGL on ROCm.
|
||||
@@ -291,17 +335,14 @@ Instead of listing them all, support is grouped into the following categories to
|
||||
* DGL Sparse
|
||||
* GraphBolt
|
||||
|
||||
.. _dgl-unsupported-features-latest:
|
||||
|
||||
Unsupported features with ROCm 7.0.0
|
||||
Unsupported features
|
||||
================================================================================
|
||||
|
||||
* TF32 Support (only supported for PyTorch 2.7 and above)
|
||||
* Kineto/ROCTracer integration
|
||||
|
||||
.. _dgl-unsupported-functions:
|
||||
|
||||
Unsupported functions with ROCm 7.0.0
|
||||
Unsupported functions
|
||||
================================================================================
|
||||
|
||||
* ``bfs``
|
||||
@@ -314,50 +355,6 @@ Unsupported functions with ROCm 7.0.0
|
||||
* ``sample_labors_noprob``
|
||||
* ``sparse_admin``
|
||||
|
||||
.. _dgl-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
DGL can be used for Graph Learning, and building popular graph models like
|
||||
GAT, GCN, and GraphSage. Using these models, a variety of use cases are supported:
|
||||
|
||||
- Recommender systems
|
||||
- Network Optimization and Analysis
|
||||
- 1D (Temporal) and 2D (Image) Classification
|
||||
- Drug Discovery
|
||||
|
||||
For use cases and recommendations, refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__,
|
||||
where you can search for DGL examples and best practices to optimize your workloads on AMD GPUs.
|
||||
|
||||
* Although multiple use cases of DGL have been tested and verified, a few have been
|
||||
outlined in the `DGL in the Real World: Running GNNs on Real Use Cases
|
||||
<https://rocm.blogs.amd.com/artificial-intelligence/dgl_blog2/README.html>`__ blog
|
||||
post, which walks through four real-world graph neural network (GNN) workloads
|
||||
implemented with the Deep Graph Library on ROCm. It covers tasks ranging from
|
||||
heterogeneous e-commerce graphs and multiplex networks (GATNE) to molecular graph
|
||||
regression (GNN-FiLM) and EEG-based neurological diagnosis (EEG-GCNN). For each use
|
||||
case, the authors detail: the dataset and task, how DGL is used, and their experience
|
||||
porting to ROCm. It is shown that DGL codebases often run without modification, with
|
||||
seamless integration of graph operations, message passing, sampling, and convolution.
|
||||
|
||||
* The `Graph Neural Networks (GNNs) at Scale: DGL with ROCm on AMD Hardware
|
||||
<https://rocm.blogs.amd.com/artificial-intelligence/why-graph-neural/README.html>`__
|
||||
blog post introduces the Deep Graph Library (DGL) and its enablement on the AMD ROCm platform,
|
||||
bringing high-performance graph neural network (GNN) training to AMD GPUs. DGL bridges
|
||||
the gap between dense tensor frameworks and the irregular nature of graph data through a
|
||||
graph-first, message-passing abstraction. Its design ensures scalability, flexibility, and
|
||||
interoperability across frameworks like PyTorch and TensorFlow. AMD’s ROCm integration
|
||||
enables DGL to run efficiently on HIP-based GPUs, supported by prebuilt Docker containers
|
||||
and open-source repositories. This marks a major step in AMD's mission to advance open,
|
||||
scalable AI ecosystems beyond traditional architectures.
|
||||
|
||||
You can pre-process datasets and begin training on AMD GPUs through:
|
||||
|
||||
* Single-GPU training/inference
|
||||
* Multi-GPU training
|
||||
|
||||
|
||||
Previous versions
|
||||
===============================================================================
|
||||
See :doc:`rocm-install-on-linux:install/3rd-party/previous-versions/dgl-history` to find documentation for previous releases
|
||||
|
||||
@@ -42,9 +42,38 @@ Support overview
|
||||
- You can also consult the upstream `Installation guide <https://docs.flashinfer.ai/installation.html>`__
|
||||
for additional context.
|
||||
|
||||
Version support
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
FlashInfer is supported on `ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__.
|
||||
|
||||
Supported devices
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
**Officially Supported**: AMD Instinct™ MI300X
|
||||
|
||||
|
||||
.. _flashinfer-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
This release of FlashInfer on ROCm provides the decode functionality for LLM inferencing.
|
||||
In the decode phase, tokens are generated sequentially, with the model predicting each new
|
||||
token based on the previously generated tokens and the input context.
|
||||
|
||||
FlashInfer on ROCm brings over upstream features such as load balancing, sparse and dense
|
||||
attention optimizations, and batching support, enabling efficient execution on AMD Instinct™ MI300X GPUs.
|
||||
|
||||
Because large LLMs often require substantial KV caches or long context windows, FlashInfer on ROCm
|
||||
also implements cascade attention from upstream to reduce memory usage.
|
||||
|
||||
For currently supported use cases and recommendations, refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__,
|
||||
where you can search for examples and best practices to optimize your workloads on AMD GPUs.
|
||||
|
||||
.. _flashinfer-docker-compat:
|
||||
|
||||
Compatibility matrix
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
@@ -66,7 +95,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- PyTorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
- GPU
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -76,23 +104,5 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `2.7.1 <https://github.com/ROCm/pytorch/releases/tag/v2.7.1>`__
|
||||
- 24.04
|
||||
- `3.12 <https://www.python.org/downloads/release/python-3129/>`__
|
||||
- MI300X
|
||||
|
||||
.. _flashinfer-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
The release of FlashInfer on ROCm provides the decode functionality for LLM inferencing.
|
||||
In the decode phase, tokens are generated sequentially, with the model predicting each new
|
||||
token based on the previously generated tokens and the input context.
|
||||
|
||||
FlashInfer on ROCm brings over upstream features such as load balancing, sparse and dense
|
||||
attention optimizations, and batching support, enabling efficient execution on AMD Instinct™ MI300X GPUs.
|
||||
|
||||
Because large LLMs often require substantial KV caches or long context windows, FlashInfer on ROCm
|
||||
also implements cascade attention from upstream to reduce memory usage.
|
||||
|
||||
For currently supported use cases and recommendations, refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__,
|
||||
where you can search for examples and best practices to optimize your workloads on AMD GPUs.
|
||||
|
||||
|
||||
@@ -56,9 +56,6 @@ between JAX Plugin–PJRT and JAX/JAXLIB.
|
||||
* - JAX Plugin-PJRT
|
||||
- JAX/JAXLIB
|
||||
- ROCm
|
||||
* - 0.8.0
|
||||
- 0.8.0
|
||||
- 7.2.0
|
||||
* - 0.7.1
|
||||
- 0.7.1
|
||||
- 7.1.1, 7.1.0
|
||||
@@ -272,33 +269,6 @@ For a complete and up-to-date list of JAX public modules (for example, ``jax.num
|
||||
JAX API modules are maintained by the JAX project and is subject to change.
|
||||
Refer to the official Jax documentation for the most up-to-date information.
|
||||
|
||||
Key features and enhancements for ROCm 7.1
|
||||
===============================================================================
|
||||
|
||||
- Enabled compilation of multihost HLO runner Python bindings.
|
||||
|
||||
- Backported multihost HLO runner bindings and some related changes to
|
||||
:code:`FunctionalHloRunner`.
|
||||
|
||||
- Added :code:`requirements_lock_3_12` to enable building for Python 3.12.
|
||||
|
||||
- Removed hardcoded NHWC convolution layout for ``fp16`` precision to address the performance drops for ``fp16`` precision on gfx12xx GPUs.
|
||||
|
||||
|
||||
- ROCprofiler-SDK integration:
|
||||
|
||||
- Integrated ROCprofiler-SDK (v3) to XLA to improve profiling of GPU events,
|
||||
support both time-based and step-based profiling.
|
||||
|
||||
- Added unit tests for :code:`rocm_collector` and :code:`rocm_tracer`.
|
||||
|
||||
- Added Triton unsupported conversion from ``f8E4M3FNUZ`` to ``fp16`` with
|
||||
rounding mode.
|
||||
|
||||
- Introduced :code:`CudnnFusedConvDecomposer` to revert fused convolutions
|
||||
when :code:`ConvAlgorithmPicker` fails to find a fused algorithm, and removed
|
||||
unfused fallback paths from :code:`RocmFusedConvRunner`.
|
||||
|
||||
Key features and enhancements for ROCm 7.0
|
||||
===============================================================================
|
||||
|
||||
|
||||
@@ -36,9 +36,47 @@ Support overview
|
||||
- You can also consult the upstream `Installation guide <https://github.com/ggml-org/llama.cpp/blob/master/docs/build.md>`__
|
||||
for additional context.
|
||||
|
||||
Version support
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
llama.cpp is supported on `ROCm 7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__ and
|
||||
`ROCm 6.4.x <https://repo.radeon.com/rocm/apt/6.4/>`__.
|
||||
|
||||
Supported devices
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
**Officially Supported**: AMD Instinct™ MI325X, MI300X, MI210
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
llama.cpp can be applied in a variety of scenarios, particularly when you need to meet one or more of the following requirements:
|
||||
|
||||
- Plain C/C++ implementation with no external dependencies
|
||||
- Support for 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory usage
|
||||
- Custom HIP (Heterogeneous-compute Interface for Portability) kernels for running large language models (LLMs) on AMD GPUs (graphics processing units)
|
||||
- CPU (central processing unit) + GPU (graphics processing unit) hybrid inference for partially accelerating models larger than the total available VRAM (video random-access memory)
|
||||
|
||||
llama.cpp is also used in a range of real-world applications, including:
|
||||
|
||||
- Games such as `Lucy's Labyrinth <https://github.com/MorganRO8/Lucys_Labyrinth>`__:
|
||||
A simple maze game where AI-controlled agents attempt to trick the player.
|
||||
- Tools such as `Styled Lines <https://marketplace.unity.com/packages/tools/ai-ml-integration/style-text-webgl-ios-stand-alone-llm-llama-cpp-wrapper-292902>`__:
|
||||
A proprietary, asynchronous inference wrapper for Unity3D game development, including pre-built mobile and web platform wrappers and a model example.
|
||||
- Various other AI applications use llama.cpp as their inference engine;
|
||||
for a detailed list, see the `user interfaces (UIs) section <https://github.com/ggml-org/llama.cpp?tab=readme-ov-file#description>`__.
|
||||
|
||||
For more use cases and recommendations, refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__,
|
||||
where you can search for llama.cpp examples and best practices to optimize your workloads on AMD GPUs.
|
||||
|
||||
- The `Llama.cpp Meets Instinct: A New Era of Open-Source AI Acceleration <https://rocm.blogs.amd.com/ecosystems-and-partners/llama-cpp/README.html>`__
|
||||
blog post outlines how the open-source llama.cpp framework enables efficient LLM inference—including interactive inference with ``llama-cli``,
|
||||
server deployment with ``llama-server``, GGUF model preparation and quantization, performance benchmarking, and optimizations tailored for
|
||||
AMD Instinct GPUs within the ROCm ecosystem.
|
||||
|
||||
.. _llama-cpp-docker-compat:
|
||||
|
||||
Compatibility matrix
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
@@ -68,7 +106,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- llama.cpp
|
||||
- ROCm
|
||||
- Ubuntu
|
||||
- GPU
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -82,7 +119,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6652 <https://github.com/ROCm/llama.cpp/tree/release/b6652>`__
|
||||
- `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
|
||||
- 24.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -96,7 +132,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6652 <https://github.com/ROCm/llama.cpp/tree/release/b6652>`__
|
||||
- `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
|
||||
- 22.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -110,7 +145,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
|
||||
- `6.4.3 <https://repo.radeon.com/rocm/apt/6.4.3/>`__
|
||||
- 24.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -124,7 +158,7 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
|
||||
- `6.4.3 <https://repo.radeon.com/rocm/apt/6.4.3/>`__
|
||||
- 22.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -138,7 +172,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
|
||||
- `6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`__
|
||||
- 24.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -152,7 +185,7 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
|
||||
- `6.4.2 <https://repo.radeon.com/rocm/apt/6.4.2/>`__
|
||||
- 22.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -166,7 +199,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
|
||||
- `6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__
|
||||
- 24.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -180,7 +212,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b6356 <https://github.com/ROCm/llama.cpp/tree/release/b6356>`__
|
||||
- `6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__
|
||||
- 22.04
|
||||
- MI325X, MI300X, MI210
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -194,9 +225,7 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `b5997 <https://github.com/ROCm/llama.cpp/tree/release/b5997>`__
|
||||
- `6.4.0 <https://repo.radeon.com/rocm/apt/6.4/>`__
|
||||
- 24.04
|
||||
- MI300X, MI210
|
||||
|
||||
.. _llama-cpp-key-rocm-libraries:
|
||||
|
||||
Key ROCm libraries for llama.cpp
|
||||
================================================================================
|
||||
@@ -239,36 +268,6 @@ your corresponding ROCm version.
|
||||
- Can be used to enhance the flash attention performance on AMD compute, by enabling
|
||||
the flag during compile time.
|
||||
|
||||
.. _llama-cpp-uses-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
llama.cpp can be applied in a variety of scenarios, particularly when you need to meet one or more of the following requirements:
|
||||
|
||||
- Plain C/C++ implementation with no external dependencies
|
||||
- Support for 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory usage
|
||||
- Custom HIP (Heterogeneous-compute Interface for Portability) kernels for running large language models (LLMs) on AMD GPUs (graphics processing units)
|
||||
- CPU (central processing unit) + GPU (graphics processing unit) hybrid inference for partially accelerating models larger than the total available VRAM (video random-access memory)
|
||||
|
||||
llama.cpp is also used in a range of real-world applications, including:
|
||||
|
||||
- Games such as `Lucy's Labyrinth <https://github.com/MorganRO8/Lucys_Labyrinth>`__:
|
||||
A simple maze game where AI-controlled agents attempt to trick the player.
|
||||
- Tools such as `Styled Lines <https://marketplace.unity.com/packages/tools/ai-ml-integration/style-text-webgl-ios-stand-alone-llm-llama-cpp-wrapper-292902>`__:
|
||||
A proprietary, asynchronous inference wrapper for Unity3D game development, including pre-built mobile and web platform wrappers and a model example.
|
||||
- Various other AI applications use llama.cpp as their inference engine;
|
||||
for a detailed list, see the `user interfaces (UIs) section <https://github.com/ggml-org/llama.cpp?tab=readme-ov-file#description>`__.
|
||||
|
||||
For more use cases and recommendations, refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__,
|
||||
where you can search for llama.cpp examples and best practices to optimize your workloads on AMD GPUs.
|
||||
|
||||
- The `Llama.cpp Meets Instinct: A New Era of Open-Source AI Acceleration <https://rocm.blogs.amd.com/ecosystems-and-partners/llama-cpp/README.html>`__
|
||||
blog post outlines how the open-source llama.cpp framework enables efficient LLM inference—including interactive inference with ``llama-cli``,
|
||||
server deployment with ``llama-server``, GGUF model preparation and quantization, performance benchmarking, and optimizations tailored for
|
||||
AMD Instinct GPUs within the ROCm ecosystem.
|
||||
|
||||
|
||||
Previous versions
|
||||
===============================================================================
|
||||
See :doc:`rocm-install-on-linux:install/3rd-party/previous-versions/llama-cpp-history` to find documentation for previous releases
|
||||
|
||||
@@ -33,44 +33,19 @@ Support overview
|
||||
- You can also consult the upstream `Installation guide <https://github.com/databricks/megablocks>`__
|
||||
for additional context.
|
||||
|
||||
.. _megablocks-docker-compat:
|
||||
Version support
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
Compatibility matrix
|
||||
================================================================================
|
||||
Megablocks is supported on `ROCm 6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`__.
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
Supported devices
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
<i class="fab fa-docker"></i>
|
||||
- **Officially Supported**: AMD Instinct™ MI300X
|
||||
- **Partially Supported** (functionality or performance limitations): AMD Instinct™ MI250X, MI210
|
||||
|
||||
AMD validates and publishes `Megablocks images <https://hub.docker.com/r/rocm/megablocks/tags>`__
|
||||
with ROCm backends on Docker Hub. The following Docker image tag and associated
|
||||
inventories represent the latest available Megablocks version from the official Docker Hub.
|
||||
Click |docker-icon| to view the image on Docker Hub.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:class: docker-image-compatibility
|
||||
|
||||
* - Docker image
|
||||
- ROCm
|
||||
- Megablocks
|
||||
- PyTorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
- GPU
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/megablocks/megablocks-0.7.0_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-372ff89b96599019b8f5f9db469c84add2529b713456781fa62eb9a148659ab4"><i class="fab fa-docker fa-lg"></i> rocm/megablocks</a>
|
||||
- `6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_
|
||||
- `0.7.0 <https://github.com/databricks/megablocks/releases/tag/v0.7.0>`_
|
||||
- `2.4.0 <https://github.com/ROCm/pytorch/tree/release/2.4>`_
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`_
|
||||
- MI300X
|
||||
|
||||
Supported models and features with ROCm 6.3.0
|
||||
================================================================================
|
||||
Supported models and features
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
This section summarizes the Megablocks features supported by ROCm.
|
||||
|
||||
@@ -102,3 +77,38 @@ It features how to pre-process datasets and how to begin pre-training on AMD GPU
|
||||
* Single-GPU pre-training
|
||||
* Multi-GPU pre-training
|
||||
|
||||
.. _megablocks-docker-compat:
|
||||
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
|
||||
<i class="fab fa-docker"></i>
|
||||
|
||||
AMD validates and publishes `Megablocks images <https://hub.docker.com/r/rocm/megablocks/tags>`__
|
||||
with ROCm backends on Docker Hub. The following Docker image tag and associated
|
||||
inventories represent the latest available Megablocks version from the official Docker Hub.
|
||||
Click |docker-icon| to view the image on Docker Hub.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:class: docker-image-compatibility
|
||||
|
||||
* - Docker image
|
||||
- ROCm
|
||||
- Megablocks
|
||||
- PyTorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/megablocks/megablocks-0.7.0_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-372ff89b96599019b8f5f9db469c84add2529b713456781fa62eb9a148659ab4"><i class="fab fa-docker fa-lg"></i> rocm/megablocks</a>
|
||||
- `6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_
|
||||
- `0.7.0 <https://github.com/databricks/megablocks/releases/tag/v0.7.0>`_
|
||||
- `2.4.0 <https://github.com/ROCm/pytorch/tree/release/2.4>`_
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`_
|
||||
|
||||
|
||||
|
||||
@@ -12,8 +12,8 @@ Ray compatibility
|
||||
|
||||
Ray is a unified framework for scaling AI and Python applications from your laptop
|
||||
to a full cluster, without changing your code. Ray consists of `a core distributed
|
||||
runtime <https://docs.ray.io/en/latest/ray-core/walkthrough.html>`__ and a set of
|
||||
`AI libraries <https://docs.ray.io/en/latest/ray-air/getting-started.html>`__ for
|
||||
runtime <https://docs.ray.io/en/latest/ray-core/walkthrough.html>`_ and a set of
|
||||
`AI libraries <https://docs.ray.io/en/latest/ray-air/getting-started.html>`_ for
|
||||
simplifying machine learning computations.
|
||||
|
||||
Ray is a general-purpose framework that runs many types of workloads efficiently.
|
||||
@@ -29,57 +29,25 @@ Support overview
|
||||
- To get started and install Ray on ROCm, use the prebuilt :ref:`Docker image <ray-docker-compat>`,
|
||||
which includes ROCm, Ray, and all required dependencies.
|
||||
|
||||
- See the :doc:`ROCm Ray installation guide <rocm-install-on-linux:install/3rd-party/ray-install>`
|
||||
- The Docker image provided is based on the upstream Ray `Daily Release (Nightly) wheels
|
||||
<https://docs.ray.io/en/latest/ray-overview/installation.html#daily-releases-nightlies>`__
|
||||
corresponding to commit `005c372 <https://github.com/ray-project/ray/commit/005c372262e050d5745f475e22e64305fa07f8b8>`__.
|
||||
|
||||
- See the :doc:`ROCm Ray installation guide <rocm-install-on-linux:install/3rd-party/ray-install>`
|
||||
for installation and setup instructions.
|
||||
|
||||
- You can also consult the upstream `Installation guide <https://docs.ray.io/en/latest/ray-overview/installation.html>`__
|
||||
for additional context.
|
||||
|
||||
.. _ray-docker-compat:
|
||||
Version support
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
Compatibility matrix
|
||||
================================================================================
|
||||
Ray is supported on `ROCm 6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__.
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
Supported devices
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
<i class="fab fa-docker"></i>
|
||||
|
||||
AMD validates and publishes `ROCm Ray Docker images <https://hub.docker.com/r/rocm/ray/tags>`__
|
||||
with ROCm backends on Docker Hub. The following Docker image tags and
|
||||
associated inventories represent the latest Ray version from the official Docker Hub.
|
||||
Click |docker-icon| to view the image on Docker Hub.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:class: docker-image-compatibility
|
||||
|
||||
* - Docker image
|
||||
- ROCm
|
||||
- Ray
|
||||
- Pytorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
- GPU
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/ray/ray-2.51.1_rocm7.0.0_ubuntu22.04_py3.12_pytorch2.9.0/images/sha256-a02f6766b4ba406f88fd7e85707ec86c04b569834d869a08043ec9bcbd672168"><i class="fab fa-docker fa-lg"></i> rocm/ray</a>
|
||||
- `7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__
|
||||
- `2.51.1 <https://github.com/ROCm/ray/tree/release/2.51.1>`__
|
||||
- 2.9.0a0+git1c57644
|
||||
- 22.04
|
||||
- `3.12.12 <https://www.python.org/downloads/release/python-31212/>`__
|
||||
- MI300X
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/ray/ray-2.48.0.post0_rocm6.4.1_ubuntu24.04_py3.12_pytorch2.6.0/images/sha256-0d166fe6bdced38338c78eedfb96eff92655fb797da3478a62dd636365133cc0"><i class="fab fa-docker fa-lg"></i> rocm/ray</a>
|
||||
- `6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__
|
||||
- `2.48.0.post0 <https://github.com/ROCm/ray/tree/release/2.48.0.post0>`__
|
||||
- 2.6.0+git684f6f2
|
||||
- 24.04
|
||||
- `3.12.10 <https://www.python.org/downloads/release/python-31210/>`__
|
||||
- MI300X, MI210
|
||||
**Officially Supported**: AMD Instinct™ MI300X, MI210
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
@@ -108,7 +76,36 @@ topic <https://docs.ray.io/en/latest/ray-core/scheduling/accelerators.html#accel
|
||||
of the Ray core documentation and refer to the `AMD ROCm blog <https://rocm.blogs.amd.com/>`__,
|
||||
where you can search for Ray examples and best practices to optimize your workloads on AMD GPUs.
|
||||
|
||||
Previous versions
|
||||
===============================================================================
|
||||
See :doc:`rocm-install-on-linux:install/3rd-party/previous-versions/ray-history` to find documentation for previous releases
|
||||
of the ``ROCm/ray`` Docker image.
|
||||
.. _ray-docker-compat:
|
||||
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
|
||||
<i class="fab fa-docker"></i>
|
||||
|
||||
AMD validates and publishes ready-made `ROCm Ray Docker images <https://hub.docker.com/r/rocm/ray/tags>`__
|
||||
with ROCm backends on Docker Hub. The following Docker image tags and
|
||||
associated inventories represent the latest Ray version from the official Docker Hub.
|
||||
Click the |docker-icon| icon to view the image on Docker Hub.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:class: docker-image-compatibility
|
||||
|
||||
* - Docker image
|
||||
- ROCm
|
||||
- Ray
|
||||
- Pytorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/ray/ray-2.48.0.post0_rocm6.4.1_ubuntu24.04_py3.12_pytorch2.6.0/images/sha256-0d166fe6bdced38338c78eedfb96eff92655fb797da3478a62dd636365133cc0"><i class="fab fa-docker fa-lg"></i> rocm/ray</a>
|
||||
- `6.4.1 <https://repo.radeon.com/rocm/apt/6.4.1/>`__.
|
||||
- `2.48.0.post0 <https://github.com/ROCm/ray/tree/release/2.48.0.post0>`_
|
||||
- 2.6.0+git684f6f2
|
||||
- 24.04
|
||||
- `3.12.10 <https://www.python.org/downloads/release/python-31210/>`_
|
||||
|
||||
@@ -35,45 +35,19 @@ Support overview
|
||||
- You can also consult the upstream `Installation guide <https://github.com/NVIDIA/Megatron-LM>`__
|
||||
for additional context.
|
||||
|
||||
.. _megatron-lm-docker-compat:
|
||||
Version support
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
Compatibility matrix
|
||||
================================================================================
|
||||
Stanford Megatron-LM is supported on `ROCm 6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`__.
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
Supported devices
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
<i class="fab fa-docker"></i>
|
||||
- **Officially Supported**: AMD Instinct™ MI300X
|
||||
- **Partially Supported** (functionality or performance limitations): AMD Instinct™ MI250X, MI210
|
||||
|
||||
AMD validates and publishes `Stanford Megatron-LM images <https://hub.docker.com/r/rocm/stanford-megatron-lm/tags>`_
|
||||
with ROCm and Pytorch backends on Docker Hub. The following Docker image tags and associated
|
||||
inventories represent the latest Stanford Megatron-LM version from the official Docker Hub.
|
||||
Click |docker-icon| to view the image on Docker Hub.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:class: docker-image-compatibility
|
||||
|
||||
* - Docker image
|
||||
- ROCm
|
||||
- Stanford Megatron-LM
|
||||
- PyTorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
- GPU
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/stanford-megatron-lm/stanford-megatron-lm85f95ae_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-070556f078be10888a1421a2cb4f48c29f28b02bfeddae02588d1f7fc02a96a6"><i class="fab fa-docker fa-lg"></i> rocm/stanford-megatron-lm</a>
|
||||
|
||||
- `6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_
|
||||
- `85f95ae <https://github.com/stanford-futuredata/Megatron-LM/commit/85f95aef3b648075fe6f291c86714fdcbd9cd1f5>`_
|
||||
- `2.4.0 <https://github.com/ROCm/pytorch/tree/release/2.4>`_
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`_
|
||||
- MI300X
|
||||
|
||||
Supported models and features with ROCm 6.3.0
|
||||
================================================================================
|
||||
Supported models and features
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
This section details models & features that are supported by the ROCm version on Stanford Megatron-LM.
|
||||
|
||||
@@ -114,3 +88,41 @@ It features how to pre-process datasets and how to begin pre-training on AMD GPU
|
||||
|
||||
* Single-GPU pre-training
|
||||
* Multi-GPU pre-training
|
||||
|
||||
.. _megatron-lm-docker-compat:
|
||||
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
|
||||
<i class="fab fa-docker"></i>
|
||||
|
||||
AMD validates and publishes `Stanford Megatron-LM images <https://hub.docker.com/r/rocm/stanford-megatron-lm/tags>`_
|
||||
with ROCm and Pytorch backends on Docker Hub. The following Docker image tags and associated
|
||||
inventories represent the latest Stanford Megatron-LM version from the official Docker Hub.
|
||||
Click |docker-icon| to view the image on Docker Hub.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:class: docker-image-compatibility
|
||||
|
||||
* - Docker image
|
||||
- ROCm
|
||||
- Stanford Megatron-LM
|
||||
- PyTorch
|
||||
- Ubuntu
|
||||
- Python
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
<a href="https://hub.docker.com/layers/rocm/stanford-megatron-lm/stanford-megatron-lm85f95ae_rocm6.3.0_ubuntu24.04_py3.12_pytorch2.4.0/images/sha256-070556f078be10888a1421a2cb4f48c29f28b02bfeddae02588d1f7fc02a96a6"><i class="fab fa-docker fa-lg"></i></a>
|
||||
|
||||
- `6.3.0 <https://repo.radeon.com/rocm/apt/6.3/>`_
|
||||
- `85f95ae <https://github.com/stanford-futuredata/Megatron-LM/commit/85f95aef3b648075fe6f291c86714fdcbd9cd1f5>`_
|
||||
- `2.4.0 <https://github.com/ROCm/pytorch/tree/release/2.4>`_
|
||||
- 24.04
|
||||
- `3.12.9 <https://www.python.org/downloads/release/python-3129/>`_
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -37,9 +37,67 @@ Support overview
|
||||
- You can also consult the upstream `verl documentation <https://verl.readthedocs.io/en/latest/>`__
|
||||
for additional context.
|
||||
|
||||
Version support
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
verl is supported on `ROCm 7.0.0 <https://repo.radeon.com/rocm/apt/7.0/>`__ and
|
||||
`ROCm 6.2.0 <https://repo.radeon.com/rocm/apt/6.2/>`__.
|
||||
|
||||
Supported devices
|
||||
--------------------------------------------------------------------------------
|
||||
|
||||
**Officially Supported**: AMD Instinct™ MI300X
|
||||
|
||||
.. _verl-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
* The benefits of verl in large-scale reinforcement learning from human feedback
|
||||
(RLHF) are discussed in the `Reinforcement Learning from Human Feedback on AMD
|
||||
GPUs with verl and ROCm Integration <https://rocm.blogs.amd.com/artificial-intelligence/verl-large-scale/README.html>`__
|
||||
blog. The blog post outlines how the Volcano Engine Reinforcement Learning
|
||||
(verl) framework integrates with the AMD ROCm platform to optimize training on
|
||||
AMD Instinct™ GPUs. The guide details the process of building a Docker image,
|
||||
setting up single-node and multi-node training environments, and highlights
|
||||
performance benchmarks demonstrating improved throughput and convergence accuracy.
|
||||
This resource serves as a comprehensive starting point for deploying verl on AMD GPUs,
|
||||
facilitating efficient RLHF training workflows.
|
||||
|
||||
.. _verl-supported_features:
|
||||
|
||||
Supported features
|
||||
===============================================================================
|
||||
|
||||
The following table shows verl on ROCm support for GPU-accelerated modules.
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
|
||||
* - Module
|
||||
- Description
|
||||
- verl version
|
||||
- ROCm version
|
||||
* - ``FSDP``
|
||||
- Training engine
|
||||
-
|
||||
* 0.6.0
|
||||
* 0.3.0.post0
|
||||
-
|
||||
* 7.0.0
|
||||
* 6.2.0
|
||||
* - ``vllm``
|
||||
- Inference engine
|
||||
-
|
||||
* 0.6.0
|
||||
* 0.3.0.post0
|
||||
-
|
||||
* 7.0.0
|
||||
* 6.2.0
|
||||
|
||||
.. _verl-docker-compat:
|
||||
|
||||
Compatibility matrix
|
||||
Docker image compatibility
|
||||
================================================================================
|
||||
|
||||
.. |docker-icon| raw:: html
|
||||
@@ -62,7 +120,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- PyTorch
|
||||
- Python
|
||||
- vllm
|
||||
- GPU
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -73,7 +130,6 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `2.9.0 <https://github.com/ROCm/pytorch/tree/release/2.9-rocm7.x-gfx115x>`__
|
||||
- `3.12.11 <https://www.python.org/downloads/release/python-31211/>`__
|
||||
- `0.11.0 <https://github.com/vllm-project/vllm/releases/tag/v0.11.0>`__
|
||||
- MI300X
|
||||
|
||||
* - .. raw:: html
|
||||
|
||||
@@ -84,33 +140,7 @@ Click |docker-icon| to view the image on Docker Hub.
|
||||
- `2.5.0 <https://github.com/ROCm/pytorch/tree/release/2.5>`__
|
||||
- `3.9.19 <https://www.python.org/downloads/release/python-3919/>`__
|
||||
- `0.6.3 <https://github.com/vllm-project/vllm/releases/tag/v0.6.3>`__
|
||||
- MI300X
|
||||
|
||||
.. _verl-supported_features:
|
||||
|
||||
Supported modules with verl on ROCm
|
||||
===============================================================================
|
||||
|
||||
The following GPU-accelerated modules are supported with verl on ROCm:
|
||||
|
||||
- ``FSDP``: Training engine
|
||||
- ``vllm``: Inference engine
|
||||
|
||||
.. _verl-recommendations:
|
||||
|
||||
Use cases and recommendations
|
||||
================================================================================
|
||||
|
||||
* The benefits of verl in large-scale reinforcement learning from human feedback
|
||||
(RLHF) are discussed in the `Reinforcement Learning from Human Feedback on AMD
|
||||
GPUs with verl and ROCm Integration <https://rocm.blogs.amd.com/artificial-intelligence/verl-large-scale/README.html>`__
|
||||
blog. The blog post outlines how the Volcano Engine Reinforcement Learning
|
||||
(verl) framework integrates with the AMD ROCm platform to optimize training on
|
||||
AMD Instinct™ GPUs. The guide details the process of building a Docker image,
|
||||
setting up single-node and multi-node training environments, and highlights
|
||||
performance benchmarks demonstrating improved throughput and convergence accuracy.
|
||||
This resource serves as a comprehensive starting point for deploying verl on AMD GPUs,
|
||||
facilitating efficient RLHF training workflows.
|
||||
|
||||
Previous versions
|
||||
===============================================================================
|
||||
|
||||
@@ -93,15 +93,15 @@ project = "ROCm Documentation"
|
||||
project_path = os.path.abspath(".").replace("\\", "/")
|
||||
author = "Advanced Micro Devices, Inc."
|
||||
copyright = "Copyright (c) 2025 Advanced Micro Devices, Inc. All rights reserved."
|
||||
version = "7.2.0"
|
||||
release = "7.2.0"
|
||||
version = "7.1.1"
|
||||
release = "7.1.1"
|
||||
setting_all_article_info = True
|
||||
all_article_info_os = ["linux", "windows"]
|
||||
all_article_info_author = ""
|
||||
|
||||
# pages with specific settings
|
||||
article_pages = [
|
||||
{"file": "about/release-notes", "os": ["linux"], "date": "2026-01-21"},
|
||||
{"file": "about/release-notes", "os": ["linux"], "date": "2025-11-26"},
|
||||
{"file": "release/changelog", "os": ["linux"],},
|
||||
{"file": "compatibility/compatibility-matrix", "os": ["linux"]},
|
||||
{"file": "compatibility/ml-compatibility/pytorch-compatibility", "os": ["linux"]},
|
||||
|
||||
@@ -8,303 +8,6 @@ dockers:
|
||||
hipBLASLt: 1.0.0
|
||||
dockerfile:
|
||||
commit: 8398684622109c806a35d660647060b0b9910663
|
||||
|
||||
configs:
|
||||
default:
|
||||
## DeepSeek AITER MLA currently only supports --block-size 1
|
||||
- &deepseek-r1-serving
|
||||
benchmark: serving
|
||||
model: deepseek-ai/DeepSeek-R1-0528
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1 8 32 128
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
block-size: 1
|
||||
## gpt-oss requires AITER unified attention and performs best with block-size 64 and FULL_AND_PIECEWISE cudagraph mode
|
||||
- &gpt-oss-120b-serving
|
||||
benchmark: serving
|
||||
model: openai/gpt-oss-120b
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1 8 32 128
|
||||
env:
|
||||
VLLM_ROCM_USE_AITER_MHA: 0
|
||||
VLLM_ROCM_USE_AITER_UNIFIED_ATTENTION: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
block-size: 64
|
||||
compilation-config: '{\"cudagraph_mode\":\"FULL_AND_PIECEWISE\"}'
|
||||
- &llama-3-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
meta-llama/Llama-3.1-405B-Instruct
|
||||
amd/Llama-3.1-405B-Instruct-FP8-KV
|
||||
meta-llama/Llama-3.3-70B-Instruct
|
||||
amd/Llama-3.3-70B-Instruct-FP8-KV
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1 8 32 128
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
## Llama 3.x MXFP4 (gfx950 only)
|
||||
- &llama-3-mxfp4-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
amd/Llama-3.1-405B-Instruct-MXFP4-Preview
|
||||
amd/Llama-3.3-70B-Instruct-MXFP4-Preview
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1 8 32 128
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
## Llama 4 currently does not support full cudagraph or attn fusion
|
||||
- &llama-4-fp8-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1 8 32 128
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
compilation-config: '{\"cudagraph_mode\":\"PIECEWISE\",\"pass_config\":{\"enable_attn_fusion\":false}}'
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
- &mixtral-8x22b-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
mistralai/Mixtral-8x22B-Instruct-v0.1
|
||||
amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1 8 32 128
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
extended:
|
||||
## gpt-oss requires AITER unified attention and performs best with block-size 64 and FULL_AND_PIECEWISE cudagraph mode
|
||||
- &gpt-oss-20b-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
openai/gpt-oss-20b
|
||||
tp: 1
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1
|
||||
env:
|
||||
VLLM_ROCM_USE_AITER_MHA: 0
|
||||
VLLM_ROCM_USE_AITER_UNIFIED_ATTENTION: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
block-size: 64
|
||||
compilation-config: '{\"cudagraph_mode\":\"FULL_AND_PIECEWISE\"}'
|
||||
- &llama-3-8b-phi-4-qwen3-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
meta-llama/Llama-3.1-8B-Instruct
|
||||
amd/Llama-3.1-8B-Instruct-FP8-KV
|
||||
microsoft/phi-4
|
||||
Qwen/Qwen3-8B
|
||||
Qwen/Qwen3-32B
|
||||
Qwen/Qwen3-30B-A3B-Thinking-2507
|
||||
Qwen/Qwen3-30B-A3B-Thinking-2507-FP8
|
||||
tp: 1
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
|
||||
- &llama-2-70b-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
meta-llama/Llama-2-70b-chat-hf
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
## Llama 4 currently does not support full cudagraph or attn fusion
|
||||
- &llama-4-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
meta-llama/Llama-4-Scout-17B-16E-Instruct
|
||||
meta-llama/Llama-4-Maverick-17B-128E-Instruct
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
compilation-config: '{\"cudagraph_mode\":\"PIECEWISE\",\"pass_config\":{\"enable_attn_fusion\":false}}'
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
|
||||
- &mixtral-8x7b-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
mistralai/Mixtral-8x7B-Instruct-v0.1
|
||||
amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
## Qwen 235B requires --enable-expert-parallel with tp 8
|
||||
- &qwen3-235b-a22b-serving
|
||||
benchmark: serving
|
||||
model:
|
||||
Qwen/Qwen3-235B-A22B-Thinking-2507
|
||||
Qwen/Qwen3-235B-A22B-Thinking-2507-FP8
|
||||
tp: 8
|
||||
inp: 1024
|
||||
out: 1024
|
||||
dtype: auto
|
||||
max_concurrency: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
enable-expert-parallel: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
accuracy:
|
||||
## DeepSeek AITER MLA currently only supports --block-size 1
|
||||
- &deepseek-r1-accuracy
|
||||
benchmark: accuracy
|
||||
model: deepseek-ai/DeepSeek-R1-0528
|
||||
tp: 8
|
||||
dtype: auto
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
block-size: 1
|
||||
bench_args:
|
||||
apply_chat_template: True
|
||||
## gpt-oss requires AITER unified attention and performs best with block-size 64 and FULL_AND_PIECEWISE cudagraph mode
|
||||
- &gpt-oss-120b-accuracy
|
||||
benchmark: accuracy
|
||||
model: openai/gpt-oss-120b
|
||||
tp: 8
|
||||
dtype: auto
|
||||
env:
|
||||
VLLM_ROCM_USE_AITER_MHA: 0
|
||||
VLLM_USE_AITER_UNIFIED_ATTENTION: 1
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
block-size: 64
|
||||
compilation-config: '{\"cudagraph_mode\":\"FULL_AND_PIECEWISE\"}'
|
||||
bench_args:
|
||||
apply_chat_template: True
|
||||
## Llama 3.x bf16 and fp8 perform better with --dtype float16 on gfx942
|
||||
- &llama-3-accuracy
|
||||
benchmark: accuracy
|
||||
model:
|
||||
meta-llama/Llama-3.1-405B-Instruct
|
||||
amd/Llama-3.1-405B-Instruct-FP8-KV
|
||||
meta-llama/Llama-3.3-70B-Instruct
|
||||
amd/Llama-3.3-70B-Instruct-FP8-KV
|
||||
tp: 8
|
||||
dtype: auto
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
bench_args:
|
||||
apply_chat_template: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
## Llama 3.x MXFP4 (gfx950 only)
|
||||
- &llama-3-mxfp4-accuracy
|
||||
benchmark: accuracy
|
||||
model:
|
||||
amd/Llama-3.1-405B-Instruct-MXFP4-Preview
|
||||
amd/Llama-3.3-70B-Instruct-MXFP4-Preview
|
||||
tp: 8
|
||||
dtype: auto
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
bench_args:
|
||||
apply_chat_template: True
|
||||
## Llama 4 currently does not support full cudagraph or attn fusion
|
||||
- &llama-4-fp8-accuracy
|
||||
benchmark: accuracy
|
||||
model:
|
||||
meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8
|
||||
tp: 8
|
||||
dtype: auto
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
compilation-config: '{\"cudagraph_mode\":\"PIECEWISE\",\"pass_config\":{\"enable_attn_fusion\":false}}'
|
||||
bench_args:
|
||||
apply_chat_template: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
## Mistral models require --tokenizer-mode mistral for correct decoding
|
||||
- &mixtral-8x22b-accuracy
|
||||
benchmark: accuracy
|
||||
model:
|
||||
mistralai/Mixtral-8x22B-Instruct-v0.1
|
||||
amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
|
||||
tp: 8
|
||||
dtype: auto
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
bench_args:
|
||||
apply_chat_template: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
## Qwen 235B requires --enable-expert-parallel with tp 8
|
||||
- &qwen3-235b-a22b-accuracy
|
||||
benchmark: accuracy
|
||||
model:
|
||||
Qwen/Qwen3-235B-A22B-Thinking-2507
|
||||
Qwen/Qwen3-235B-A22B-Thinking-2507-FP8
|
||||
dtype: auto
|
||||
extra_args:
|
||||
async-scheduling: True
|
||||
enable-expert-parallel: True
|
||||
bench_args:
|
||||
apply_chat_template: True
|
||||
arch_overrides:
|
||||
gfx942:
|
||||
dtype: float16
|
||||
|
||||
model_groups:
|
||||
- group: Meta Llama
|
||||
tag: llama
|
||||
@@ -315,139 +18,132 @@ model_groups:
|
||||
url: https://huggingface.co/meta-llama/Llama-2-70b-chat-hf
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-2-70b-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 4096
|
||||
max_model_len: 4096
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 4096
|
||||
max_model_len: 4096
|
||||
- model: Llama 3.1 8B
|
||||
mad_tag: pyt_vllm_llama-3.1-8b
|
||||
model_repo: meta-llama/Llama-3.1-8B-Instruct
|
||||
url: https://huggingface.co/meta-llama/Llama-3.1-8B
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-8b-phi-4-qwen3-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 3.1 8B FP8
|
||||
mad_tag: pyt_vllm_llama-3.1-8b_fp8
|
||||
model_repo: amd/Llama-3.1-8B-Instruct-FP8-KV
|
||||
url: https://huggingface.co/amd/Llama-3.1-8B-Instruct-FP8-KV
|
||||
precision: float8
|
||||
config:
|
||||
serving: *llama-3-8b-phi-4-qwen3-serving
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 3.1 405B
|
||||
mad_tag: pyt_vllm_llama-3.1-405b
|
||||
model_repo: meta-llama/Llama-3.1-405B-Instruct
|
||||
url: https://huggingface.co/meta-llama/Llama-3.1-405B-Instruct
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-serving
|
||||
accuracy: *llama-3-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 3.1 405B FP8
|
||||
mad_tag: pyt_vllm_llama-3.1-405b_fp8
|
||||
model_repo: amd/Llama-3.1-405B-Instruct-FP8-KV
|
||||
url: https://huggingface.co/amd/Llama-3.1-405B-Instruct-FP8-KV
|
||||
precision: float8
|
||||
config:
|
||||
serving: *llama-3-serving
|
||||
accuracy: *llama-3-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 3.1 405B MXFP4
|
||||
mad_tag: pyt_vllm_llama-3.1-405b_fp4
|
||||
model_repo: amd/Llama-3.1-405B-Instruct-MXFP4-Preview
|
||||
url: https://huggingface.co/amd/Llama-3.1-405B-Instruct-MXFP4-Preview
|
||||
precision: float4
|
||||
config:
|
||||
serving: *llama-3-mxfp4-serving
|
||||
accuracy: *llama-3-mxfp4-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 3.3 70B
|
||||
mad_tag: pyt_vllm_llama-3.3-70b
|
||||
model_repo: meta-llama/Llama-3.3-70B-Instruct
|
||||
url: https://huggingface.co/meta-llama/Llama-3.3-70B-Instruct
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-serving
|
||||
accuracy: *llama-3-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 3.3 70B FP8
|
||||
mad_tag: pyt_vllm_llama-3.3-70b_fp8
|
||||
model_repo: amd/Llama-3.3-70B-Instruct-FP8-KV
|
||||
url: https://huggingface.co/amd/Llama-3.3-70B-Instruct-FP8-KV
|
||||
precision: float8
|
||||
config:
|
||||
serving: *llama-3-serving
|
||||
accuracy: *llama-3-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 3.3 70B MXFP4
|
||||
mad_tag: pyt_vllm_llama-3.3-70b_fp4
|
||||
model_repo: amd/Llama-3.3-70B-Instruct-MXFP4-Preview
|
||||
url: https://huggingface.co/amd/Llama-3.3-70B-Instruct-MXFP4-Preview
|
||||
precision: float4
|
||||
config:
|
||||
serving: *llama-3-mxfp4-serving
|
||||
accuracy: *llama-3-mxfp4-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- model: Llama 4 Scout 17Bx16E
|
||||
mad_tag: pyt_vllm_llama-4-scout-17b-16e
|
||||
model_repo: meta-llama/Llama-4-Scout-17B-16E-Instruct
|
||||
url: https://huggingface.co/meta-llama/Llama-4-Scout-17B-16E-Instruct
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-4-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
- model: Llama 4 Maverick 17Bx128E
|
||||
mad_tag: pyt_vllm_llama-4-maverick-17b-128e
|
||||
model_repo: meta-llama/Llama-4-Maverick-17B-128E-Instruct
|
||||
url: https://huggingface.co/meta-llama/Llama-4-Maverick-17B-128E-Instruct
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-4-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
- model: Llama 4 Maverick 17Bx128E FP8
|
||||
mad_tag: pyt_vllm_llama-4-maverick-17b-128e_fp8
|
||||
model_repo: meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8
|
||||
url: https://huggingface.co/meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8
|
||||
precision: float8
|
||||
config:
|
||||
serving: *llama-4-fp8-serving
|
||||
accuracy: *llama-4-fp8-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- group: DeepSeek
|
||||
tag: deepseek
|
||||
models:
|
||||
@@ -457,12 +153,12 @@ model_groups:
|
||||
url: https://huggingface.co/deepseek-ai/DeepSeek-R1-0528
|
||||
precision: float8
|
||||
config:
|
||||
serving: *deepseek-r1-serving
|
||||
accuracy: *deepseek-r1-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_seqs: 1024
|
||||
max_num_batched_tokens: 131072
|
||||
max_model_len: 8192
|
||||
- group: OpenAI GPT OSS
|
||||
tag: gpt-oss
|
||||
models:
|
||||
@@ -472,23 +168,22 @@ model_groups:
|
||||
url: https://huggingface.co/openai/gpt-oss-20b
|
||||
precision: bfloat16
|
||||
config:
|
||||
serving: *gpt-oss-20b-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 8192
|
||||
max_model_len: 8192
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 8192
|
||||
max_model_len: 8192
|
||||
- model: GPT OSS 120B
|
||||
mad_tag: pyt_vllm_gpt-oss-120b
|
||||
model_repo: openai/gpt-oss-120b
|
||||
url: https://huggingface.co/openai/gpt-oss-120b
|
||||
precision: bfloat16
|
||||
config:
|
||||
serving: *gpt-oss-120b-serving
|
||||
accuracy: *gpt-oss-120b-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 8192
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 8192
|
||||
max_model_len: 8192
|
||||
- group: Mistral AI
|
||||
tag: mistral
|
||||
models:
|
||||
@@ -498,46 +193,44 @@ model_groups:
|
||||
url: https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
|
||||
precision: float16
|
||||
config:
|
||||
serving: *mixtral-8x7b-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
- model: Mixtral MoE 8x7B FP8
|
||||
mad_tag: pyt_vllm_mixtral-8x7b_fp8
|
||||
model_repo: amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV
|
||||
url: https://huggingface.co/amd/Mixtral-8x7B-Instruct-v0.1-FP8-KV
|
||||
precision: float8
|
||||
config:
|
||||
serving: *mixtral-8x7b-serving
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 32768
|
||||
max_model_len: 8192
|
||||
- model: Mixtral MoE 8x22B
|
||||
mad_tag: pyt_vllm_mixtral-8x22b
|
||||
model_repo: mistralai/Mixtral-8x22B-Instruct-v0.1
|
||||
url: https://huggingface.co/mistralai/Mixtral-8x22B-Instruct-v0.1
|
||||
precision: float16
|
||||
config:
|
||||
serving: *mixtral-8x22b-serving
|
||||
accuracy: *mixtral-8x22b-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 65536
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 65536
|
||||
max_model_len: 8192
|
||||
- model: Mixtral MoE 8x22B FP8
|
||||
mad_tag: pyt_vllm_mixtral-8x22b_fp8
|
||||
model_repo: amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
|
||||
url: https://huggingface.co/amd/Mixtral-8x22B-Instruct-v0.1-FP8-KV
|
||||
precision: float8
|
||||
config:
|
||||
serving: *mixtral-8x22b-serving
|
||||
accuracy: *mixtral-8x22b-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 65536
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 65536
|
||||
max_model_len: 8192
|
||||
- group: Qwen
|
||||
tag: qwen
|
||||
models:
|
||||
@@ -547,68 +240,66 @@ model_groups:
|
||||
url: https://huggingface.co/Qwen/Qwen3-8B
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-8b-phi-4-qwen3-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 32B
|
||||
mad_tag: pyt_vllm_qwen3-32b
|
||||
model_repo: Qwen/Qwen3-32B
|
||||
model_repo: Qwen/Qwen3-32b
|
||||
url: https://huggingface.co/Qwen/Qwen3-32B
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-8b-phi-4-qwen3-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 30B A3B Thinking
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 30B A3B
|
||||
mad_tag: pyt_vllm_qwen3-30b-a3b
|
||||
model_repo: Qwen/Qwen3-30B-A3B-Thinking-2507
|
||||
url: https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507
|
||||
model_repo: Qwen/Qwen3-30B-A3B
|
||||
url: https://huggingface.co/Qwen/Qwen3-30B-A3B
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-8b-phi-4-qwen3-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 30B A3B Thinking FP8
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 30B A3B FP8
|
||||
mad_tag: pyt_vllm_qwen3-30b-a3b_fp8
|
||||
model_repo: Qwen/Qwen3-30B-A3B-Thinking-2507-FP8
|
||||
url: https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507-FP8
|
||||
model_repo: Qwen/Qwen3-30B-A3B-FP8
|
||||
url: https://huggingface.co/Qwen/Qwen3-30B-A3B-FP8
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-8b-phi-4-qwen3-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 235B A22B Thinking
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 235B A22B
|
||||
mad_tag: pyt_vllm_qwen3-235b-a22b
|
||||
model_repo: Qwen/Qwen3-235B-A22B-Thinking-2507
|
||||
url: https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507
|
||||
model_repo: Qwen/Qwen3-235B-A22B
|
||||
url: https://huggingface.co/Qwen/Qwen3-235B-A22B
|
||||
precision: float16
|
||||
config:
|
||||
serving: *qwen3-235b-a22b-serving
|
||||
accuracy: *qwen3-235b-a22b-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 235B A22B Thinking FP8
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- model: Qwen3 235B A22B FP8
|
||||
mad_tag: pyt_vllm_qwen3-235b-a22b_fp8
|
||||
model_repo: Qwen/Qwen3-235B-A22B-Thinking-2507-FP8
|
||||
url: https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507-FP8
|
||||
model_repo: Qwen/Qwen3-235B-A22B-FP8
|
||||
url: https://huggingface.co/Qwen/Qwen3-235B-A22B-FP8
|
||||
precision: float8
|
||||
config:
|
||||
serving: *qwen3-235b-a22b-serving
|
||||
accuracy: *qwen3-235b-a22b-accuracy
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
tp: 8
|
||||
dtype: auto
|
||||
kv_cache_dtype: fp8
|
||||
max_num_batched_tokens: 40960
|
||||
max_model_len: 8192
|
||||
- group: Microsoft Phi
|
||||
tag: phi
|
||||
models:
|
||||
@@ -618,8 +309,8 @@ model_groups:
|
||||
url: https://huggingface.co/microsoft/phi-4
|
||||
precision: float16
|
||||
config:
|
||||
serving: *llama-3-8b-phi-4-qwen3-serving
|
||||
ex:
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 16384
|
||||
max_model_len: 8192
|
||||
tp: 1
|
||||
dtype: auto
|
||||
kv_cache_dtype: auto
|
||||
max_num_batched_tokens: 16384
|
||||
max_model_len: 8192
|
||||
|
||||
@@ -19,95 +19,117 @@ The table below summarizes information about ROCm-enabled deep learning framewor
|
||||
:widths: 5 3 6 3
|
||||
|
||||
* - Framework
|
||||
- Installation guide
|
||||
- Installation
|
||||
- Installation options
|
||||
- GitHub
|
||||
|
||||
* - :doc:`PyTorch <../compatibility/ml-compatibility/pytorch-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/pytorch-install>`
|
||||
* - `PyTorch <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/pytorch-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- Wheels package
|
||||
- ROCm Base Docker image
|
||||
- Upstream Docker file
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-a-docker-image-with-pytorch-pre-installed>`__
|
||||
- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-a-wheels-package>`__
|
||||
- `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-the-pytorch-rocm-base-docker-image>`__
|
||||
- `Upstream Docker file <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/pytorch-install.html#using-the-pytorch-upstream-dockerfile>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/pytorch"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`TensorFlow <../compatibility/ml-compatibility/tensorflow-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/tensorflow-install>`
|
||||
* - `TensorFlow <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/tensorflow-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- Wheels package
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html#using-a-docker-image-with-tensorflow-pre-installed>`__
|
||||
- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/tensorflow-install.html#using-a-wheels-package>`__
|
||||
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/tensorflow-upstream"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`JAX <../compatibility/ml-compatibility/jax-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/jax-install>`
|
||||
* - `JAX <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/jax-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/jax-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/jax-install.html#using-a-prebuilt-docker-image>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/jax"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`verl <../compatibility/ml-compatibility/verl-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/verl-install>`
|
||||
* - `verl <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/verl-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/verl-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/verl-install.html#use-a-prebuilt-docker-image-with-verl-pre-installed>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/verl"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`Stanford Megatron-LM <../compatibility/ml-compatibility/stanford-megatron-lm-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/stanford-megatron-lm-install>`
|
||||
* - `Stanford Megatron-LM <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/stanford-megatron-lm-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/stanford-megatron-lm-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/stanford-megatron-lm-install.html#use-a-prebuilt-docker-image-with-stanford-megatron-lm-pre-installed>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/Stanford-Megatron-LM"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`DGL <../compatibility/ml-compatibility/dgl-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/dgl-install>`
|
||||
* - `DGL <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/dgl-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/dgl-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/dgl-install.html#use-a-prebuilt-docker-image-with-dgl-pre-installed>`__
|
||||
- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/dgl-install.html#use-a-wheels-package>`__
|
||||
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/dgl"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`Megablocks <../compatibility/ml-compatibility/megablocks-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/megablocks-install>`
|
||||
* - `Megablocks <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/megablocks-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/megablocks-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/megablocks-install.html#using-a-prebuilt-docker-image-with-megablocks-pre-installed>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/megablocks"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`Ray <../compatibility/ml-compatibility/ray-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/ray-install>`
|
||||
* - `Ray <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/ray-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/ray-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- Wheels package
|
||||
- ROCm Base Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/ray-install.html#using-a-prebuilt-docker-image-with-ray-pre-installed>`__
|
||||
- `Wheels package <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/ray-install.html#install-ray-on-bare-metal-or-a-custom-container>`__
|
||||
- `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/ray-install.html#build-your-own-docker-image>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/ray"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`llama.cpp <../compatibility/ml-compatibility/llama-cpp-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/llama-cpp-install>`
|
||||
* - `llama.cpp <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/llama-cpp-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/llama-cpp-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- ROCm Base Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/llama-cpp-install.html#use-a-prebuilt-docker-image-with-llama-cpp-pre-installed>`__
|
||||
- `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/llama-cpp-install.html#build-your-own-docker-image>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/llama.cpp"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
* - :doc:`FlashInfer <../compatibility/ml-compatibility/flashinfer-compatibility>`
|
||||
- :doc:`link <rocm-install-on-linux:install/3rd-party/flashinfer-install>`
|
||||
* - `FlashInfer <https://rocm.docs.amd.com/en/latest/compatibility/ml-compatibility/flashinfer-compatibility.html>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/flashinfer-install.html"><i class="fas fa-link fa-lg"></i></a>
|
||||
-
|
||||
- Docker image
|
||||
- ROCm Base Docker image
|
||||
- `Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/flashinfer-install.html#use-a-prebuilt-docker-image-with-flashinfer-pre-installed>`__
|
||||
- `ROCm Base Docker image <https://rocm.docs.amd.com/projects/install-on-linux/en/latest/install/3rd-party/flashinfer-install.html#build-your-own-docker-image>`__
|
||||
- .. raw:: html
|
||||
|
||||
<a href="https://github.com/ROCm/flashinfer"><i class="fab fa-github fa-lg"></i></a>
|
||||
|
||||
@@ -44,7 +44,7 @@ Setting up the base implementation environment
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
amd-smi static --board
|
||||
rocm-smi --showproductname
|
||||
|
||||
#. Check that your GPUs are available to PyTorch.
|
||||
|
||||
@@ -65,8 +65,8 @@ Setting up the base implementation environment
|
||||
|
||||
.. tip::
|
||||
|
||||
During training and inference, you can check the memory usage by running the ``amd-smi`` command in your terminal.
|
||||
This tool helps you see which GPUs are involved.
|
||||
During training and inference, you can check the memory usage by running the ``rocm-smi`` command in your terminal.
|
||||
This tool helps you see shows which GPUs are involved.
|
||||
|
||||
|
||||
.. _fine-tuning-llms-multi-gpu-hugging-face-accelerate:
|
||||
@@ -91,10 +91,10 @@ Now, it's important to adjust how you load the model. Add the ``device_map`` par
|
||||
|
||||
...
|
||||
base_model_name = "meta-llama/Llama-2-7b-chat-hf"
|
||||
|
||||
|
||||
# Load base model to GPU memory
|
||||
base_model = AutoModelForCausalLM.from_pretrained(
|
||||
base_model_name,
|
||||
base_model_name,
|
||||
device_map = "auto",
|
||||
trust_remote_code = True)
|
||||
...
|
||||
@@ -139,7 +139,7 @@ model fine-tuning and inference with LLMs.
|
||||
|
||||
# Install torchtune with PyTorch release 2.2.2+
|
||||
pip install torchtune
|
||||
|
||||
|
||||
# To confirm that the package is installed correctly
|
||||
tune --help
|
||||
|
||||
@@ -148,12 +148,12 @@ model fine-tuning and inference with LLMs.
|
||||
.. code-block:: shell
|
||||
|
||||
usage: tune [-h] {download,ls,cp,run,validate} ...
|
||||
|
||||
|
||||
Welcome to the TorchTune CLI!
|
||||
|
||||
|
||||
options:
|
||||
-h, --help show this help message and exit
|
||||
|
||||
|
||||
subcommands:
|
||||
{download,ls,cp,run,validate}
|
||||
|
||||
@@ -194,11 +194,11 @@ model fine-tuning and inference with LLMs.
|
||||
apply_lora_to_output: False
|
||||
lora_rank: 8
|
||||
lora_alpha: 16
|
||||
|
||||
|
||||
tokenizer:
|
||||
_component_: torchtune.models.llama2.llama2_tokenizer
|
||||
path: /tmp/Llama-2-7b-hf/tokenizer.model
|
||||
|
||||
|
||||
# Dataset and sampler
|
||||
dataset:
|
||||
_component_: torchtune.datasets.alpaca_cleaned_dataset
|
||||
|
||||
@@ -44,19 +44,20 @@ Setting up the base implementation environment
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
amd-smi static --board
|
||||
rocm-smi --showproductname
|
||||
|
||||
Your output should look like this:
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
GPU: 0
|
||||
BOARD:
|
||||
MODEL_NUMBER: 102-G39203-0B
|
||||
PRODUCT_SERIAL: PCB079220-1150
|
||||
FRU_ID: 113-AMDG392030B04-100-300000097H
|
||||
PRODUCT_NAME: AMD Instinct MI325 OAM
|
||||
MANUFACTURER_NAME: AMD
|
||||
============================ ROCm System Management Interface ============================
|
||||
====================================== Product Info ======================================
|
||||
GPU[0] : Card Series: AMD Instinct MI300X OAM
|
||||
GPU[0] : Card model: 0x74a1
|
||||
GPU[0] : Card vendor: Advanced Micro Devices, Inc. [AMD/ATI]
|
||||
GPU[0] : Card SKU: MI3SRIOV
|
||||
==========================================================================================
|
||||
================================== End of ROCm SMI Log ===================================
|
||||
|
||||
#. Check that your GPUs are available to PyTorch.
|
||||
|
||||
@@ -93,13 +94,13 @@ Setting up the base implementation environment
|
||||
pip install -r requirements-dev.txt
|
||||
cmake -DBNB_ROCM_ARCH="gfx942" -DCOMPUTE_BACKEND=hip -S .
|
||||
python setup.py install
|
||||
|
||||
|
||||
# To leverage the SFTTrainer in TRL for model fine-tuning.
|
||||
pip install trl
|
||||
|
||||
|
||||
# To leverage PEFT for efficiently adapting pre-trained language models .
|
||||
pip install peft
|
||||
|
||||
|
||||
# Install the other dependencies.
|
||||
pip install transformers datasets huggingface-hub scipy
|
||||
|
||||
@@ -131,7 +132,7 @@ Download the base model and fine-tuning dataset
|
||||
|
||||
.. note::
|
||||
|
||||
You can also use the `NousResearch Llama-2-7b-chat-hf <https://huggingface.co/NousResearch/Llama-2-7b-chat-hf>`_
|
||||
You can also use the `NousResearch Llama-2-7b-chat-hf <https://huggingface.co/NousResearch/Llama-2-7b-chat-hf>`_
|
||||
as a substitute. It has the same model weights as the original.
|
||||
|
||||
#. Run the following code to load the base model and tokenizer.
|
||||
@@ -140,14 +141,14 @@ Download the base model and fine-tuning dataset
|
||||
|
||||
# Base model and tokenizer names.
|
||||
base_model_name = "meta-llama/Llama-2-7b-chat-hf"
|
||||
|
||||
|
||||
# Load base model to GPU memory.
|
||||
device = "cuda:0"
|
||||
base_model = AutoModelForCausalLM.from_pretrained(base_model_name, trust_remote_code = True).to(device)
|
||||
|
||||
|
||||
# Load tokenizer.
|
||||
tokenizer = AutoTokenizer.from_pretrained(
|
||||
base_model_name,
|
||||
base_model_name,
|
||||
trust_remote_code = True)
|
||||
tokenizer.pad_token = tokenizer.eos_token
|
||||
tokenizer.padding_side = "right"
|
||||
@@ -161,10 +162,10 @@ Download the base model and fine-tuning dataset
|
||||
# Dataset for fine-tuning.
|
||||
training_dataset_name = "mlabonne/guanaco-llama2-1k"
|
||||
training_dataset = load_dataset(training_dataset_name, split = "train")
|
||||
|
||||
|
||||
# Check the data.
|
||||
print(training_dataset)
|
||||
|
||||
|
||||
# Dataset 11 is a QA sample in English.
|
||||
print(training_dataset[11])
|
||||
|
||||
@@ -251,8 +252,8 @@ Compare the number of trainable parameters and training time under the two diffe
|
||||
dataset_text_field = "text",
|
||||
tokenizer = tokenizer,
|
||||
args = training_arguments
|
||||
)
|
||||
|
||||
)
|
||||
|
||||
# Run the trainer.
|
||||
sft_trainer.train()
|
||||
|
||||
@@ -285,7 +286,7 @@ Compare the number of trainable parameters and training time under the two diffe
|
||||
if param.requires_grad:
|
||||
trainable_params += param.numel()
|
||||
print(f"trainable params: {trainable_params} || all params: {all_param} || trainable%: {100 * trainable_params / all_param:.2f}")
|
||||
|
||||
|
||||
sft_trainer.peft_config = None
|
||||
print_trainable_parameters(sft_trainer.model)
|
||||
|
||||
@@ -308,8 +309,8 @@ Compare the number of trainable parameters and training time under the two diffe
|
||||
dataset_text_field = "text",
|
||||
tokenizer = tokenizer,
|
||||
args = training_arguments
|
||||
)
|
||||
|
||||
)
|
||||
|
||||
# Training.
|
||||
trainer_full.train()
|
||||
|
||||
@@ -348,7 +349,7 @@ store, and load.
|
||||
|
||||
# PEFT adapter name.
|
||||
adapter_name = "llama-2-7b-enhanced-adapter"
|
||||
|
||||
|
||||
# Save PEFT adapter.
|
||||
sft_trainer.model.save_pretrained(adapter_name)
|
||||
|
||||
@@ -358,21 +359,21 @@ store, and load.
|
||||
|
||||
# Access adapter directory.
|
||||
cd llama-2-7b-enhanced-adapter
|
||||
|
||||
|
||||
# List all adapter files.
|
||||
README.md adapter_config.json adapter_model.safetensors
|
||||
|
||||
.. tab-item:: Saving a fully fine-tuned model
|
||||
:sync: without
|
||||
|
||||
If you're not using LoRA and PEFT so there is no PEFT LoRA configuration used for training, use the following code
|
||||
If you're not using LoRA and PEFT so there is no PEFT LoRA configuration used for training, use the following code
|
||||
to save your fine-tuned model to your system.
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
# Fully fine-tuned model name.
|
||||
new_model_name = "llama-2-7b-enhanced"
|
||||
|
||||
|
||||
# Save the fully fine-tuned model.
|
||||
full_trainer.model.save_pretrained(new_model_name)
|
||||
|
||||
@@ -382,7 +383,7 @@ store, and load.
|
||||
|
||||
# Access new model directory.
|
||||
cd llama-2-7b-enhanced
|
||||
|
||||
|
||||
# List all model files.
|
||||
config.json model-00002-of-00006.safetensors model-00005-of-00006.safetensors
|
||||
generation_config.json model-00003-of-00006.safetensors model-00006-of-00006.safetensors
|
||||
@@ -411,26 +412,26 @@ Let's look at achieving model inference using these types of models.
|
||||
|
||||
.. tab-item:: Inference using PEFT adapters
|
||||
|
||||
To use PEFT adapters like a normal transformer model, you can run the generation by loading a base model along with PEFT
|
||||
To use PEFT adapters like a normal transformer model, you can run the generation by loading a base model along with PEFT
|
||||
adapters as follows.
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
from peft import PeftModel
|
||||
from transformers import AutoModelForCausalLM
|
||||
|
||||
|
||||
# Set the path of the model or the name on Hugging face hub
|
||||
base_model_name = "meta-llama/Llama-2-7b-chat-hf"
|
||||
|
||||
|
||||
# Set the path of the adapter
|
||||
adapter_name = "Llama-2-7b-enhanced-adpater"
|
||||
|
||||
# Load base model
|
||||
|
||||
# Load base model
|
||||
base_model = AutoModelForCausalLM.from_pretrained(base_model_name)
|
||||
|
||||
# Adapt the base model with the adapter
|
||||
|
||||
# Adapt the base model with the adapter
|
||||
new_model = PeftModel.from_pretrained(base_model, adapter_name)
|
||||
|
||||
|
||||
# Then, run generation as the same with a normal model outlined in 2.1
|
||||
|
||||
The PEFT library provides a ``merge_and_unload`` method, which merges the adapter layers into the base model. This is
|
||||
@@ -438,13 +439,13 @@ Let's look at achieving model inference using these types of models.
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
# Load base model
|
||||
# Load base model
|
||||
base_model = AutoModelForCausalLM.from_pretrained(base_model_name)
|
||||
|
||||
# Adapt the base model with the adapter
|
||||
|
||||
# Adapt the base model with the adapter
|
||||
new_model = PeftModel.from_pretrained(base_model, adapter_name)
|
||||
|
||||
# Merge adapter
|
||||
|
||||
# Merge adapter
|
||||
model = model.merge_and_unload()
|
||||
|
||||
# Save the merged model into local
|
||||
@@ -460,25 +461,25 @@ Let's look at achieving model inference using these types of models.
|
||||
|
||||
# Import relevant class for loading model and tokenizer
|
||||
from transformers import AutoTokenizer, AutoModelForCausalLM
|
||||
|
||||
|
||||
# Set the pre-trained model name on Hugging face hub
|
||||
model_name = "meta-llama/Llama-2-7b-chat-hf"
|
||||
|
||||
# Set device type
|
||||
|
||||
# Set device type
|
||||
device = "cuda:0"
|
||||
|
||||
# Load model and tokenizer
|
||||
|
||||
# Load model and tokenizer
|
||||
model = AutoModelForCausalLM.from_pretrained(model_name).to(device)
|
||||
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
||||
|
||||
# Input prompt encoding
|
||||
|
||||
# Input prompt encoding
|
||||
query = "What is a large language model?"
|
||||
inputs = tokenizer.encode(query, return_tensors="pt").to(device)
|
||||
|
||||
# Token generation
|
||||
outputs = model.generate(inputs)
|
||||
|
||||
# Outputs decoding
|
||||
|
||||
# Token generation
|
||||
outputs = model.generate(inputs)
|
||||
|
||||
# Outputs decoding
|
||||
print(tokenizer.decode(outputs[0]))
|
||||
|
||||
In addition, pipelines from Transformers offer simple APIs to use pre-trained models for different tasks, including
|
||||
@@ -489,14 +490,14 @@ Let's look at achieving model inference using these types of models.
|
||||
|
||||
# Import relevant class for loading model and tokenizer
|
||||
from transformers import pipeline
|
||||
|
||||
|
||||
# Set the path of your model or the name on Hugging face hub
|
||||
model_name_or_path = "meta-llama/Llama-2-7b-chat-hf"
|
||||
|
||||
# Set pipeline
|
||||
|
||||
# Set pipeline
|
||||
# A positive device value will run the model on associated CUDA device id
|
||||
pipe = pipeline("text-generation", model=model_name_or_path, device=0)
|
||||
|
||||
|
||||
# Token generation
|
||||
print(pipe("What is a large language model?")[0]["generated_text"])
|
||||
|
||||
|
||||
@@ -189,10 +189,6 @@ Benchmarking
|
||||
{% for model_group in model_groups %}
|
||||
{% for model in model_group.models %}
|
||||
|
||||
{% set serv_config = model.config.serving %}
|
||||
{% set acc_config = model.config.accuracy %}
|
||||
{% set ex_config = model.config.ex %}
|
||||
|
||||
.. container:: model-doc {{model.mad_tag}}
|
||||
|
||||
.. tab-set::
|
||||
@@ -287,173 +283,108 @@ Benchmarking
|
||||
--name test \
|
||||
{{ docker.pull_tag }}
|
||||
|
||||
.. rubric:: Run the inference benchmarks
|
||||
.. rubric:: Throughput command
|
||||
|
||||
.. tab-set::
|
||||
Use the following command to start the throughput benchmark.
|
||||
|
||||
.. tab-item:: Latency command
|
||||
.. code-block:: shell
|
||||
|
||||
Use the following command to start the latency benchmark.
|
||||
model={{ model.model_repo }}
|
||||
tp={{ model.config.tp }}
|
||||
num_prompts={{ model.config.num_prompts | default(1024) }}
|
||||
in={{ model.config.in | default(128) }}
|
||||
out={{ model.config.in | default(128) }}
|
||||
dtype={{ model.config.dtype | default("auto") }}
|
||||
kv_cache_dtype={{ model.config.kv_cache_dtype }}
|
||||
max_num_seqs={{ model.config.max_num_seqs | default(1024) }}
|
||||
max_num_batched_tokens={{ model.config.max_num_batched_tokens }}
|
||||
max_model_len={{ model.config.max_model_len }}
|
||||
|
||||
.. code-block:: shell
|
||||
vllm bench throughput --model $model \
|
||||
-tp $tp \
|
||||
--num-prompts $num_prompts \
|
||||
--input-len $in \
|
||||
--output-len $out \
|
||||
--dtype $dtype \
|
||||
--kv-cache-dtype $kv_cache_dtype \
|
||||
--max-num-seqs $max_num_seqs \
|
||||
--max-num-batched-tokens $max_num_batched_tokens \
|
||||
--max-model-len $max_model_len \
|
||||
--trust-remote-code \
|
||||
--output-json ${model}_throughput.json \
|
||||
--gpu-memory-utilization {{ model.config.gpu_memory_utilization | default(0.9) }}
|
||||
|
||||
model={{ model.model_repo }}
|
||||
tp={{ serv_config.tp }}
|
||||
batch_size=16
|
||||
in={{ serv_config.inp | default(1024) }}
|
||||
out={{ serv_config.out | default(1024) }}
|
||||
dtype={{ serv_config.dtype | default("auto") }}
|
||||
kv_cache_dtype={{ ex_config.kv_cache_dtype | default("auto") }}
|
||||
max_num_seqs={{ ex_config.max_num_seqs | default(1024) }}
|
||||
max_num_batched_tokens={{ ex_config.max_num_batched_tokens }}
|
||||
max_model_len={{ ex_config.max_model_len }}
|
||||
.. rubric:: Serving command
|
||||
|
||||
vllm bench latency --model $model \
|
||||
-tp $tp \
|
||||
--batch-size $batch_size \
|
||||
--input-len $in \
|
||||
--output-len $out \
|
||||
--dtype $dtype \
|
||||
--kv-cache-dtype $kv_cache_dtype \
|
||||
--max-num-seqs $max_num_seqs \
|
||||
--max-num-batched-tokens $max_num_batched_tokens \
|
||||
--max-model-len $max_model_len \
|
||||
--output-json ${model}_throughput.json \
|
||||
1. Start the server using the following command:
|
||||
|
||||
.. tab-item:: Throughput command
|
||||
.. code-block:: shell
|
||||
|
||||
Use the following command to start the throughput benchmark.
|
||||
model={{ model.model_repo }}
|
||||
tp={{ model.config.tp }}
|
||||
dtype={{ model.config.dtype }}
|
||||
kv_cache_dtype={{ model.config.kv_cache_dtype }}
|
||||
max_num_seqs=256
|
||||
max_num_batched_tokens={{ model.config.max_num_batched_tokens }}
|
||||
max_model_len={{ model.config.max_model_len }}
|
||||
|
||||
.. code-block:: shell
|
||||
vllm serve $model \
|
||||
-tp $tp \
|
||||
--dtype $dtype \
|
||||
--kv-cache-dtype $kv_cache_dtype \
|
||||
--max-num-seqs $max_num_seqs \
|
||||
--max-num-batched-tokens $max_num_batched_tokens \
|
||||
--max-model-len $max_model_len \
|
||||
--no-enable-prefix-caching \
|
||||
--swap-space 16 \
|
||||
--disable-log-requests \
|
||||
--trust-remote-code \
|
||||
--gpu-memory-utilization 0.9
|
||||
|
||||
model={{ model.model_repo }}
|
||||
tp={{ serv_config.tp }}
|
||||
num_prompts={{ model.config.num_prompts | default(1024) }}
|
||||
in={{ serv_config.inp | default(1024) }}
|
||||
out={{ serv_config.out | default(1024) }}
|
||||
dtype={{ serv_config.dtype | default("auto") }}
|
||||
kv_cache_dtype={{ ex_config.kv_cache_dtype | default("auto") }}
|
||||
max_num_seqs={{ ex_config.max_num_seqs | default(1024) }}
|
||||
max_num_batched_tokens={{ ex_config.max_num_batched_tokens }}
|
||||
max_model_len={{ ex_config.max_model_len }}
|
||||
Wait until the model has loaded and the server is ready to accept requests.
|
||||
|
||||
vllm bench throughput --model $model \
|
||||
-tp $tp \
|
||||
--num-prompts $num_prompts \
|
||||
--input-len $in \
|
||||
--output-len $out \
|
||||
--dtype $dtype \
|
||||
--kv-cache-dtype $kv_cache_dtype \
|
||||
--max-num-seqs $max_num_seqs \
|
||||
--max-num-batched-tokens $max_num_batched_tokens \
|
||||
--max-model-len $max_model_len \
|
||||
--trust-remote-code \
|
||||
--output-json ${model}_throughput.json \
|
||||
--gpu-memory-utilization {{ model.config.gpu_memory_utilization | default(0.9) }}
|
||||
2. On another terminal on the same machine, run the benchmark:
|
||||
|
||||
.. tab-item:: Serving command
|
||||
.. code-block:: shell
|
||||
|
||||
1. Start the server using the following command:
|
||||
# Connect to the container
|
||||
docker exec -it test bash
|
||||
|
||||
.. code-block:: shell
|
||||
# Wait for the server to start
|
||||
until curl -s http://localhost:8000/v1/models; do sleep 30; done
|
||||
|
||||
model={{ model.model_repo }}
|
||||
tp={{ serv_config.tp }}
|
||||
dtype={{ serv_config.dtype }}
|
||||
kv_cache_dtype={{ ex_config.kv_cache_dtype }}
|
||||
max_num_seqs=1024
|
||||
max_num_batched_tokens={{ ex_config.max_num_batched_tokens }}
|
||||
max_model_len={{ ex_config.max_model_len }}
|
||||
# Run the benchmark
|
||||
model={{ model.model_repo }}
|
||||
max_concurrency=1
|
||||
num_prompts=10
|
||||
in=128
|
||||
out=128
|
||||
vllm bench serve --model $model \
|
||||
--percentile-metrics "ttft,tpot,itl,e2el" \
|
||||
--dataset-name random \
|
||||
--ignore-eos \
|
||||
--max-concurrency $max_concurrency \
|
||||
--num-prompts $num_prompts \
|
||||
--random-input-len $in \
|
||||
--random-output-len $out \
|
||||
--trust-remote-code \
|
||||
--save-result \
|
||||
--result-filename ${model}_serving.json
|
||||
|
||||
vllm serve $model \
|
||||
-tp $tp \
|
||||
--dtype $dtype \
|
||||
--kv-cache-dtype $kv_cache_dtype \
|
||||
--max-num-seqs $max_num_seqs \
|
||||
--max-num-batched-tokens $max_num_batched_tokens \
|
||||
--max-model-len $max_model_len \
|
||||
--no-enable-prefix-caching \
|
||||
--swap-space 16 \
|
||||
--disable-log-requests
|
||||
.. note::
|
||||
|
||||
Wait until the model has loaded and the server is ready to accept requests.
|
||||
For improved performance with certain Mixture of Experts models, such as Mixtral 8x22B,
|
||||
try adding ``export VLLM_ROCM_USE_AITER=1`` to your commands.
|
||||
|
||||
2. On another terminal on the same machine, run the benchmark:
|
||||
If you encounter the following error, pass your access-authorized Hugging
|
||||
Face token to the gated models.
|
||||
|
||||
.. code-block:: shell
|
||||
.. code-block::
|
||||
|
||||
# Connect to the container
|
||||
docker exec -it test bash
|
||||
OSError: You are trying to access a gated repo.
|
||||
|
||||
# Wait for the server to start
|
||||
until curl -s http://localhost:8000/v1/models; do sleep 30; done
|
||||
|
||||
# Run the benchmark
|
||||
model={{ model.model_repo }}
|
||||
max_concurrency=1
|
||||
num_prompts=10
|
||||
in={{ serv_config.inp | default("1024") }}
|
||||
out={{ serv_config.out | default("1024") }}
|
||||
vllm bench serve --model $model \
|
||||
--percentile-metrics "ttft,tpot,itl,e2el" \
|
||||
--dataset-name random \
|
||||
--ignore-eos \
|
||||
--max-concurrency $max_concurrency \
|
||||
--num-prompts $num_prompts \
|
||||
--random-input-len $in \
|
||||
--random-output-len $out \
|
||||
--trust-remote-code \
|
||||
--save-result \
|
||||
--result-filename ${model}_serving.json
|
||||
|
||||
{% if acc_config %}
|
||||
.. tab-item:: Accuracy command
|
||||
|
||||
1. Start the server using the following command:
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
model={{ model.model_repo }}
|
||||
tp={{ acc_config.tp }}
|
||||
dtype={{ acc_config.dtype }}
|
||||
kv_cache_dtype={{ ex_config.kv_cache_dtype }}
|
||||
max_num_seqs=1024
|
||||
max_num_batched_tokens={{ ex_config.max_num_batched_tokens }}
|
||||
max_model_len={{ ex_config.max_model_len }}
|
||||
|
||||
vllm serve $model \
|
||||
-tp $tp \
|
||||
--dtype $dtype \
|
||||
--kv-cache-dtype $kv_cache_dtype \
|
||||
--max-num-seqs $max_num_seqs \
|
||||
--max-num-batched-tokens $max_num_batched_tokens \
|
||||
--max-model-len $max_model_len \
|
||||
--no-enable-prefix-caching \
|
||||
--swap-space 16 \
|
||||
--disable-log-requests
|
||||
|
||||
Wait until the model has loaded and the server is ready to accept requests.
|
||||
|
||||
2. On another terminal on the same machine, run the benchmark:
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
# Connect to the container
|
||||
docker exec -it test bash
|
||||
|
||||
# Wait for the server to start
|
||||
until curl -s http://localhost:8000/v1/models; do sleep 30; done
|
||||
|
||||
# Install lm-eval
|
||||
pip install lm-eval[api]
|
||||
|
||||
# Run the benchmark
|
||||
model={{ acc_config.model }}
|
||||
lm_eval --model local-completions \
|
||||
--model_args model=$model,max_gen_toks=2048,num_concurrent=256,max_retries=10,base_url=http://localhost:8000/v1/completions \
|
||||
--tasks gsm8k --limit 250 --output_path ./tmp
|
||||
|
||||
{% endif %}
|
||||
# pass your HF_TOKEN
|
||||
export HF_TOKEN=$your_personal_hf_token
|
||||
|
||||
.. raw:: html
|
||||
|
||||
|
||||
@@ -31,16 +31,16 @@ in the Instinct documentation for more information.
|
||||
Hardware verification with ROCm
|
||||
-------------------------------
|
||||
|
||||
Use the command ``amd-smi set --perf-determinism 1900`` to set the max clock speed up to 1900 MHz
|
||||
Use the command ``rocm-smi --setperfdeterminism 1900`` to set the max clock speed up to 1900 MHz
|
||||
instead of the default 2100 MHz. This can reduce the chance of a PCC event lowering the attainable
|
||||
GPU clocks. This setting will not be required for new IFWI releases with the production PRC feature.
|
||||
You can restore this setting to its default value with the ``amd-smi reset --clocks`` command.
|
||||
You can restore this setting to its default value with the ``rocm-smi -r`` command.
|
||||
|
||||
Run the command:
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
amd-smi set --perf-determinism 1900
|
||||
rocm-smi --setperfdeterminism 1900
|
||||
|
||||
See `Hardware verfication for ROCm <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html#hardware-verification-with-rocm>`_
|
||||
in the Instinct documentation for more information.
|
||||
|
||||
@@ -108,16 +108,16 @@ for more information.
|
||||
Hardware verification with ROCm
|
||||
-------------------------------
|
||||
|
||||
Use the command ``amd-smi set --perf-determinism 1900`` to set the max clock speed up to 1900 MHz
|
||||
Use the command ``rocm-smi --setperfdeterminism 1900`` to set the max clock speed up to 1900 MHz
|
||||
instead of the default 2100 MHz. This can reduce the chance of a PCC event lowering the attainable
|
||||
GPU clocks. This setting will not be required for new IFWI releases with the production PRC feature.
|
||||
You can restore this setting to its default value with the ``amd-smi reset --clocks`` command.
|
||||
You can restore this setting to its default value with the ``rocm-smi -r`` command.
|
||||
|
||||
Run the command:
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
amd-smi set --perf-determinism 1900
|
||||
rocm-smi --setperfdeterminism 1900
|
||||
|
||||
See `Hardware verification with ROCm <https://instinct.docs.amd.com/projects/amdgpu-docs/en/latest/system-optimization/mi300x.html#hardware-verification-with-rocm>`_ for more information.
|
||||
|
||||
@@ -248,7 +248,7 @@ Download the Docker image and required packages
|
||||
Checking out this specific commit is recommended for a stable and reproducible environment.
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
|
||||
git checkout bb93ccbfeae6363c67b361a97a27c74ab86e7e92
|
||||
|
||||
Prepare training datasets
|
||||
|
||||
@@ -285,7 +285,7 @@ tweak some configurations (such as batch sizes).
|
||||
|
||||
.. code-block:: shell
|
||||
|
||||
EXP=examples/torchtitan/configs/MI355X/llama3.1_8B-FP8-pretrain.yaml \
|
||||
EXP=examples/torchtitan/configs/MI355X/llama3.1_8B-BF16-pretrain.yaml \
|
||||
bash examples/run_pretrain.sh
|
||||
|
||||
.. tab-item:: MI325X
|
||||
|
||||
@@ -5,7 +5,7 @@
|
||||
GPU hardware specifications
|
||||
===========================================
|
||||
|
||||
The following tables provide an overview of the hardware specifications for AMD Instinct™ GPUs, AMD Radeon™ PRO and Radeon™ GPUs, and AMD Ryzen™ APUs.
|
||||
The following tables provide an overview of the hardware specifications for AMD Instinct™ GPUs, and AMD Radeon™ PRO and Radeon™ GPUs.
|
||||
|
||||
For more information about ROCm hardware compatibility, see the ROCm `Compatibility matrix <https://rocm.docs.amd.com/en/latest/compatibility/compatibility-matrix.html>`_.
|
||||
|
||||
@@ -18,7 +18,7 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
|
||||
:name: instinct-arch-spec-table
|
||||
|
||||
*
|
||||
- Name
|
||||
- Model
|
||||
- Architecture
|
||||
- LLVM target name
|
||||
- VRAM (GiB)
|
||||
@@ -297,7 +297,7 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
|
||||
:name: radeon-pro-arch-spec-table
|
||||
|
||||
*
|
||||
- Name
|
||||
- Model
|
||||
- Architecture
|
||||
- LLVM target name
|
||||
|
||||
@@ -333,24 +333,6 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
|
||||
- 32
|
||||
- 12
|
||||
- 0
|
||||
*
|
||||
- Radeon AI PRO R9600D
|
||||
- RDNA4
|
||||
- gfx1201
|
||||
- 32
|
||||
- 48
|
||||
- 32 or 64
|
||||
- 128
|
||||
- 48
|
||||
- 8
|
||||
- N/A
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 768
|
||||
- 32
|
||||
- 12
|
||||
- 0
|
||||
*
|
||||
- Radeon PRO V710
|
||||
- RDNA3
|
||||
@@ -557,7 +539,7 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
|
||||
:name: radeon-arch-spec-table
|
||||
|
||||
*
|
||||
- Name
|
||||
- Model
|
||||
- Architecture
|
||||
- LLVM target name
|
||||
- VRAM (GiB)
|
||||
@@ -628,24 +610,6 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
|
||||
- 32
|
||||
- 12
|
||||
- 0
|
||||
*
|
||||
- Radeon RX 9060 XT LP
|
||||
- RDNA4
|
||||
- gfx1200
|
||||
- 16
|
||||
- 32
|
||||
- 32 or 64
|
||||
- 128
|
||||
- 32
|
||||
- 4
|
||||
- N/A
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 768
|
||||
- 32
|
||||
- 12
|
||||
- 0
|
||||
*
|
||||
- Radeon RX 9060 XT
|
||||
- RDNA4
|
||||
@@ -754,24 +718,6 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
|
||||
- 32
|
||||
- 11
|
||||
- 0
|
||||
*
|
||||
- Radeon RX 7700
|
||||
- RDNA3
|
||||
- gfx1101
|
||||
- 16
|
||||
- 40
|
||||
- 32 or 64
|
||||
- 128
|
||||
- 64
|
||||
- 4
|
||||
- 256
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 768
|
||||
- 32
|
||||
- 11
|
||||
- 0
|
||||
*
|
||||
- Radeon RX 7700 XT
|
||||
- RDNA3
|
||||
@@ -1007,127 +953,6 @@ For more information about ROCm hardware compatibility, see the ROCm `Compatibil
|
||||
- 9
|
||||
- 0
|
||||
|
||||
.. tab-item:: AMD Ryzen APUs
|
||||
|
||||
.. list-table::
|
||||
:header-rows: 1
|
||||
:name: ryzen-arch-spec-table
|
||||
|
||||
*
|
||||
- Name
|
||||
- Graphics model
|
||||
- Architecture
|
||||
- LLVM target name
|
||||
- VRAM (GiB)
|
||||
- Compute Units
|
||||
- Wavefront Size
|
||||
- LDS (KiB)
|
||||
- Infinity Cache (MiB)
|
||||
- L2 Cache (MiB)
|
||||
- Graphics L1 Cache (KiB)
|
||||
- L0 Vector Cache (KiB)
|
||||
- L0 Scalar Cache (KiB)
|
||||
- L0 Instruction Cache (KiB)
|
||||
- VGPR File (KiB)
|
||||
- SGPR File (KiB)
|
||||
- GFXIP Major version
|
||||
- GFXIP Minor version
|
||||
*
|
||||
- AMD Ryzen 7 7840U
|
||||
- Radeon 780M
|
||||
- RDNA3
|
||||
- gfx1103
|
||||
- Dynamic + carveout
|
||||
- 12
|
||||
- 32 or 64
|
||||
- 128
|
||||
- N/A
|
||||
- 2
|
||||
- 256
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 512
|
||||
- 32
|
||||
- 11
|
||||
- 0
|
||||
*
|
||||
- AMD Ryzen 9 270
|
||||
- Radeon 780M
|
||||
- RDNA3
|
||||
- gfx1103
|
||||
- Dynamic + carveout
|
||||
- 12
|
||||
- 32 or 64
|
||||
- 128
|
||||
- N/A
|
||||
- 2
|
||||
- 256
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 512
|
||||
- 32
|
||||
- 11
|
||||
- 0
|
||||
*
|
||||
- AMD Ryzen AI 9 HX 375
|
||||
- Radeon 890M
|
||||
- RDNA3.5
|
||||
- gfx1150
|
||||
- Dynamic + carveout
|
||||
- 16
|
||||
- 32 or 64
|
||||
- 128
|
||||
- N/A
|
||||
- 2
|
||||
- 256
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 512
|
||||
- 32
|
||||
- 11
|
||||
- 5
|
||||
*
|
||||
- AMD Ryzen AI Max+ PRO 395
|
||||
- Radeon 8060S
|
||||
- RDNA3.5
|
||||
- gfx1151
|
||||
- Dynamic + carveout
|
||||
- 40
|
||||
- 32 or 64
|
||||
- 128
|
||||
- 32
|
||||
- 2
|
||||
- 256
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 768
|
||||
- 32
|
||||
- 11
|
||||
- 5
|
||||
*
|
||||
- AMD Ryzen Al 7 350
|
||||
- Radeon 860M
|
||||
- RDNA3.5
|
||||
- gfx1152
|
||||
- Dynamic + carveout
|
||||
- 8
|
||||
- 32 or 64
|
||||
- 128
|
||||
- N/A
|
||||
- 1
|
||||
- 256
|
||||
- 32
|
||||
- 16
|
||||
- 32
|
||||
- 512
|
||||
- 32
|
||||
- 11
|
||||
- 5
|
||||
|
||||
Glossary
|
||||
========
|
||||
|
||||
|
||||
@@ -10,7 +10,6 @@
|
||||
|
||||
| Version | Release date |
|
||||
| ------- | ------------ |
|
||||
| [7.2.0](https://rocm.docs.amd.com/en/docs-7.2.0/) | January 21, 2026 |
|
||||
| [7.1.1](https://rocm.docs.amd.com/en/docs-7.1.1/) | November 26, 2025 |
|
||||
| [7.1.0](https://rocm.docs.amd.com/en/docs-7.1.0/) | October 30, 2025 |
|
||||
| [7.0.2](https://rocm.docs.amd.com/en/docs-7.0.2/) | October 10, 2025 |
|
||||
|
||||
@@ -25,7 +25,7 @@ subtrees:
|
||||
title: HIP SDK on Windows
|
||||
- url: https://rocm.docs.amd.com/projects/radeon-ryzen/en/latest/index.html
|
||||
title: ROCm on Radeon and Ryzen
|
||||
- file: how-to/deep-learning-rocm
|
||||
- file: how-to/deep-learning-rocm.md
|
||||
title: Deep learning frameworks
|
||||
subtrees:
|
||||
- entries:
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
rocm-docs-core==1.31.3
|
||||
rocm-docs-core==1.31.1
|
||||
sphinx-reredirects
|
||||
sphinx-sitemap
|
||||
sphinxcontrib.datatemplates==0.11.0
|
||||
|
||||
@@ -19,11 +19,11 @@ babel==2.17.0
|
||||
# via
|
||||
# pydata-sphinx-theme
|
||||
# sphinx
|
||||
beautifulsoup4==4.14.3
|
||||
beautifulsoup4==4.14.2
|
||||
# via pydata-sphinx-theme
|
||||
breathe==4.36.0
|
||||
# via rocm-docs-core
|
||||
certifi==2026.1.4
|
||||
certifi==2025.11.12
|
||||
# via requests
|
||||
cffi==2.0.0
|
||||
# via
|
||||
@@ -39,7 +39,7 @@ comm==0.2.3
|
||||
# via ipykernel
|
||||
cryptography==46.0.3
|
||||
# via pyjwt
|
||||
debugpy==1.8.19
|
||||
debugpy==1.8.17
|
||||
# via ipykernel
|
||||
decorator==5.2.1
|
||||
# via ipython
|
||||
@@ -60,21 +60,21 @@ fastjsonschema==2.21.2
|
||||
# rocm-docs-core
|
||||
gitdb==4.0.12
|
||||
# via gitpython
|
||||
gitpython==3.1.46
|
||||
gitpython==3.1.45
|
||||
# via rocm-docs-core
|
||||
greenlet==3.3.0
|
||||
greenlet==3.2.4
|
||||
# via sqlalchemy
|
||||
idna==3.11
|
||||
# via requests
|
||||
imagesize==1.4.1
|
||||
# via sphinx
|
||||
importlib-metadata==8.7.1
|
||||
importlib-metadata==8.7.0
|
||||
# via
|
||||
# jupyter-cache
|
||||
# myst-nb
|
||||
ipykernel==7.1.0
|
||||
# via myst-nb
|
||||
ipython==8.38.0
|
||||
ipython==8.37.0
|
||||
# via
|
||||
# ipykernel
|
||||
# myst-nb
|
||||
@@ -84,13 +84,13 @@ jinja2==3.1.6
|
||||
# via
|
||||
# myst-parser
|
||||
# sphinx
|
||||
jsonschema==4.26.0
|
||||
jsonschema==4.25.1
|
||||
# via nbformat
|
||||
jsonschema-specifications==2025.9.1
|
||||
# via jsonschema
|
||||
jupyter-cache==1.0.1
|
||||
# via myst-nb
|
||||
jupyter-client==8.8.0
|
||||
jupyter-client==8.6.3
|
||||
# via
|
||||
# ipykernel
|
||||
# nbclient
|
||||
@@ -118,7 +118,7 @@ myst-nb==1.3.0
|
||||
# via rocm-docs-core
|
||||
myst-parser==4.0.1
|
||||
# via myst-nb
|
||||
nbclient==0.10.4
|
||||
nbclient==0.10.2
|
||||
# via
|
||||
# jupyter-cache
|
||||
# myst-nb
|
||||
@@ -138,11 +138,11 @@ parso==0.8.5
|
||||
# via jedi
|
||||
pexpect==4.9.0
|
||||
# via ipython
|
||||
platformdirs==4.5.1
|
||||
platformdirs==4.5.0
|
||||
# via jupyter-core
|
||||
prompt-toolkit==3.0.52
|
||||
# via ipython
|
||||
psutil==7.2.1
|
||||
psutil==7.1.3
|
||||
# via ipykernel
|
||||
ptyprocess==0.7.0
|
||||
# via pexpect
|
||||
@@ -188,9 +188,9 @@ requests==2.32.5
|
||||
# via
|
||||
# pygithub
|
||||
# sphinx
|
||||
rocm-docs-core==1.31.3
|
||||
rocm-docs-core==1.31.1
|
||||
# via -r requirements.in
|
||||
rpds-py==0.30.0
|
||||
rpds-py==0.29.0
|
||||
# via
|
||||
# jsonschema
|
||||
# referencing
|
||||
@@ -200,7 +200,7 @@ smmap==5.0.2
|
||||
# via gitdb
|
||||
snowballstemmer==3.0.1
|
||||
# via sphinx
|
||||
soupsieve==2.8.1
|
||||
soupsieve==2.8
|
||||
# via beautifulsoup4
|
||||
sphinx==8.1.3
|
||||
# via
|
||||
@@ -214,7 +214,6 @@ sphinx==8.1.3
|
||||
# sphinx-design
|
||||
# sphinx-external-toc
|
||||
# sphinx-last-updated-by-git
|
||||
# sphinx-multitoc-numbering
|
||||
# sphinx-notfound-page
|
||||
# sphinx-reredirects
|
||||
# sphinxcontrib-datatemplates
|
||||
@@ -225,12 +224,10 @@ sphinx-copybutton==0.5.2
|
||||
# via rocm-docs-core
|
||||
sphinx-design==0.6.1
|
||||
# via rocm-docs-core
|
||||
sphinx-external-toc==1.1.0
|
||||
sphinx-external-toc==1.0.1
|
||||
# via rocm-docs-core
|
||||
sphinx-last-updated-by-git==0.3.8
|
||||
# via sphinx-sitemap
|
||||
sphinx-multitoc-numbering==0.1.3
|
||||
# via sphinx-external-toc
|
||||
sphinx-notfound-page==1.1.0
|
||||
# via rocm-docs-core
|
||||
sphinx-reredirects==0.1.6
|
||||
@@ -253,15 +250,15 @@ sphinxcontrib-runcmd==0.2.0
|
||||
# via sphinxcontrib-datatemplates
|
||||
sphinxcontrib-serializinghtml==2.0.0
|
||||
# via sphinx
|
||||
sqlalchemy==2.0.45
|
||||
sqlalchemy==2.0.44
|
||||
# via jupyter-cache
|
||||
stack-data==0.6.3
|
||||
# via ipython
|
||||
tabulate==0.9.0
|
||||
# via jupyter-cache
|
||||
tomli==2.4.0
|
||||
tomli==2.3.0
|
||||
# via sphinx
|
||||
tornado==6.5.4
|
||||
tornado==6.5.2
|
||||
# via
|
||||
# ipykernel
|
||||
# jupyter-client
|
||||
@@ -285,7 +282,7 @@ typing-extensions==4.15.0
|
||||
# pygithub
|
||||
# referencing
|
||||
# sqlalchemy
|
||||
urllib3==2.6.3
|
||||
urllib3==2.5.0
|
||||
# via
|
||||
# pygithub
|
||||
# requests
|
||||
|
||||
Reference in New Issue
Block a user