Vectorized Sparse Matrix Multiply for Compressed Row Storage Format

Abstract

The innovation of this work is a simple vectorizable algorithm for performing sparse matrix vector multiply in compressed sparse row (CSR) storage format. Unlike the vectorizable jagged diagonal format (JAD), this algorithm requires no data rearrangement and can be easily adapted to a sophisticated library framework such as PETSc. Numerical experiments on… (More)
DOI: 10.1007/11428831_13

Topics

5 Figures and Tables

Statistics

0510'05'06'07'08'09'10'11'12'13'14'15'16'17'18
Citations per Year

58 Citations

Semantic Scholar estimates that this publication has 58 citations based on the available data.

See our FAQ for additional information.

Slides referencing similar topics