A survey of high-performance sparse matrix-vector multiplication programming
Sparse matrix-vector multiplication(SpMV)are fundamental operations in scientific computing,graph compu-tation,and data analysis.They have been an enduring and challenging research topic since the birth of modern computing.This paper systematically reviews the development of SpMV from 1970s and the representative work at each stage.It analyzes and compares four technical routes in this field:manual programming,automatic tuners,sparse compilers,and automatic programmers.These are the popular approaches today.On this basis,the paper makes predictions on the future trends of research on SpMV programs.It aims to provide useful insights to learners and researchers.
万方数据
维普
