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cusparseLt - cusparseMatMul

Description

This sample demonstrates the usage of cuSPARSELt library and cusparseMatMul APIs for performing structured matrix - dense matrix multiplication by exploiting NVIDIA Sparse Tensor Cores, where the structured matrix is compressed with 50% sparsity ratio. The sample also demonstrates the usage of batched computation, Split-K, ReLU activation function, and bias.

cusparseLt Documentation

C_i = ReLU(A_i * B_i + C_i + bias)

where A is an structured matrix, and B, C, D are dense matrices

Building

  • Linux

    make CUSPARSELT_PATH=<cusparseLt_path> CUDA_TOOLKIT_PATH=<cuda_toolkit_path>

  • or in alternative:

    mkdir build
cd build
cmake -DCUSPARSELT_PATH=<cusparseLt_path> -DCMAKE_CUDA_COMPILER=<nvcc_path> ..
make

Support

  • Supported SM Architectures: SM 8.0, SM 8.6, SM 8.9, SM 9.0
  • Supported OSes: Linux, Windows
  • Supported CPU Architectures: x86_64, arm64
  • Supported Compilers: gcc, clang, Microsoft msvc, Nvidia HPC SDK nvc
  • Language: C++14

Prerequisites