This sample demonstrates the usage of cusparseSDDMM
for performing batched dense matrix - dense matrix multiplication into sparse matrix, where the sparse matrix is represented in CSR (Compressed Sparse Row) storage format.
C = (alpha * A * B) ° spy(C) + beta * C
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Command line
nvcc -I<cuda_toolkit_path>/include sddmm_csr_batched_example.c -o sddmm_csr_batched_example -lcusparse
-
Linux
make
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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.
- 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
- CUDA 11.7.1 toolkit (or above) and compatible driver (see CUDA Driver Release Notes).
- CMake 3.9 or above on Windows