spgemm

cuSPARSE Generic APIs - cusparseSpGEMM

Description

This sample demonstrates the usage of cusparseSpGEMM for performing sparse matrix - sparse matrix multiplication, where all operands are sparse matrices represented in CSR (Compressed Sparse Row) storage format.

cusparseSpGEMM Documentation

C = alpha * A * B + beta * C

Building

• Command line

  nvcc -I<cuda_toolkit_path>/include spgemm_example.c -o spgemm_example -lcusparse

• Linux

  make

• Windows/Linux

  mkdir build
  cd build
  cmake ..
  make

  On Windows, instead of running the last build step, open the Visual Studio Solution that was created and build.

Support

• Supported SM Architectures: SM 3.5, SM 3.7, SM 5.0, SM 5.2, SM 5.3, SM 6.0, SM 6.1, SM 6.2, SM 7.0, SM 7.2, SM 7.5, SM 8.0, SM 8.6, SM 8.9, SM 9.0
• Supported OSes: Linux, Windows, QNX, Android
• Supported CPU Architectures: x86_64, ppc64le, arm64
• Supported Compilers: gcc, clang, Intel icc, IBM xlc, Microsoft msvc, Nvidia HPC SDK nvc
• Language: C99

Prerequisites

• CUDA 11.0 toolkit (or above) and compatible driver (see CUDA Driver Release Notes).
• CMake 3.9 or above on Windows