AOCL-Sparse contains basic linear algebra subroutines for sparse matrices and vectors optimized for AMD processors. It is designed to be used with C and C++.
Highlights of AOCL-Sparse 3.1
- API for Sparse Matrix Dense Matrix Multiply (SPMM) giving dense matrix output
- Supports single and double precision data types
- Supports general sparse matrices in CSR format with zero-based indexing and no transpose
- Conversion routine “CSR to Dense” that converts sparse matrix in CSR format to dense matrix format
Highlights of AOCL-Sparse 3.0
- Supports CSR, Ellpack, Diagonal, Blocked-CSR data formats for SPMV function
- New API, Sparse Triangular Solve (TRSV) for Single and Double Precision data types
- Supports General matrices with zero-based indexing and no transpose.
- New Sparse data format conversion routines:
- CSR to Ellpack
- CSR to Diagonal
- CSR to Blocked-CSR
- CSR to CSC
The packages containing AOCL-Sparse binaries, examples and documentation are available in the Downloads section below.
Source code for AOCL-Sparse will be available shortly on GitHub https://github.com/amd/aocl-sparse
Refer here for prior versions of AOCL-Sparse documentation and downloads.