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56 lines
1.8 KiB
ReStructuredText
56 lines
1.8 KiB
ReStructuredText
.. meta::
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:description: List of ROCm and CUDA supported functions in hipBLASLt
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:keywords: hipSPARSELt, ROCm, API library, API reference, supported
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functions
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.. _supported-functions:
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******************************************************
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Supported ROCm and NVIDIA CUDA functions
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******************************************************
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Here is a list of the ROCm and NVIDIA CUDA functions supported by hipBLASLt:
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* ROCm
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* AMD sparse MFMA matrix core support
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* Mixed-precision computation support:
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* ``FP16`` input/output, ``FP32`` matrix core accumulate
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* ``BFLOAT16`` input/output, ``FP32`` matrix core accumulate
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* ``INT8`` input/output, ``INT32`` matrix core accumulate
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* ``INT8`` input, ``FP16`` output, ``INT32`` matrix core accumulate
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* ``FP8`` input, ``FP32`` output, ``FP32`` matrix core accumulate
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* ``BF8`` input, ``FP32`` output, ``FP32`` matrix core accumulate
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* Matrix pruning and compression functionalities
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* Auto-tuning functionality (see ``hipsparseLtMatmulSearch()``)
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* Batched sparse GEMM support:
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* Single sparse matrix/multiple dense matrices (broadcast)
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* Multiple sparse and dense matrices
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* Batched bias vector
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* Activation function fuse in SpMM kernel support:
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* ReLU
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* ClippedReLU (ReLU with upper bound and threshold setting)
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* GeLU
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* GeLU scaling (implied enable GeLU)
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* Abs
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* LeakyReLU
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* Sigmoid
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* Tanh
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* Ongoing feature development
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* Add support for mixed-precision computation:
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* ``FP8`` input/output, ``FP32`` matrix core accumulate
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* ``BF8`` input/output, ``FP32`` matrix core accumulate
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* Add kernel selection and generator, used to provide the appropriate solution for the specific problem
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* CUDA
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* Support for CUDA cuSPARSELt v0.6.3
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