Abstract: Open source instruction set architecture RISC-V has the advantages of high performance, modularization, simplicity, easy extension, etc., and is widely used in the Internet of Things, cloud computing and other fields. The V module of its vector expansion part supports matrix numerical calculation well. As an important part of matrix numerical calculation, sparse matrix vector multiplication (SpMV) has profound research significance and value. Using the vector configurability and addressing characteristics of RISC-V instruction set, vector multiplication of sparse matrix based on CSR, ELLPACK and HYB compressed format is vectorized respectively. Meanwhile, considering that the sparse matrix is extremely sparse and the number of non-zero elements in each row fluctuates greatly, the HYB storage format is improved by compressing the storage of row vectors with low density of non-zero elements and adjusting the HYB segmentation threshold, which significantly improves the computational efficiency and storage efficiency.

Key words: RISC-V, vector expansion, sparse matrix, SpMV