Abstract:

The sparse matrix vector multiplication (SPMV) is the kernel of many scientific applications.Due to its indirect and random memory accesses,the SPMV is the bottleneck of scientific applications.In this paper,based on analyzing data structure and computation process,we present the memory access characteristics of the SPMV and propose a memory access behavior characteristicsorient cache partition method.According to the performance evaluation with 12 sparse matrix vector multiplications,the proposed cache partition method increase the hit ratio of reusable data and reduce the cache capacity request efficiently during the SPMV.

Key words: sparse matrix；vector multiplication;cache partition;memory access behavior character