ROCm & CUDA supported functions

• ROCm

  • AMD sparse MFMA matrix core support

  • Mixed-precision computation support:

    • FP16 input/output, FP32 Matrix Core accumulate

    • BFLOAT16 input/output, FP32 Matrix Core accumulate

    • INT8 input/output, INT32 Matrix Core accumulate

    • INT8 input, FP16 output, INT32 Matrix Core accumulate

  • Matrix pruning and compression functionalities

  • Auto-tuning functionality (see hipsparseLtMatmulSearch())

  • Batched sparse Gemm support:

    • Single sparse matrix/Multiple dense matrices (Broadcast)

    • Multiple sparse and dense matrices

    • Batched bias vector

  • Activation function fuse in SpMM kernel support:

    • ReLU

    • ClippedReLU (ReLU with upper bound and threshold setting)

    • GeLU

    • GeLU Scaling (Implied enable GeLU)

    • Abs

    • LeakyReLU

    • Sigmoid

    • Tanh

  • On-going feature development

    • Add support for Mixed-precision computation

      • FP8 input/output, FP32 Matrix Core accumulate

      • BF8 input/output, FP32 Matrix Core accumulate

      • Add kernel selection and generator, used to provide the appropriate solution for the specific problem.

• CUDA

  • Support cuSPARSELt v0.4