Merge-based sparse matrix-vector multiplication (SpMV) using the CSR storage format-Reference-Cited by-同舟云学术

Merge-based sparse matrix-vector multiplication (SpMV) using the CSR storage format

Published:2016-02-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
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Author:

Merrill Duane¹,Garland Michael¹

Affiliation:

1. NVIDIA Corp.

Funder

Defense Advanced Research Projects Agency

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2851141.2851190

Reference5 articles.

1. T. Davis and Y. Hu. University of Florida Sparse Matrix Collection. URL http://www.cise.ufl.edu/research/sparse/matrices/. 10.1145/2049662.2049663 T. Davis and Y. Hu. University of Florida Sparse Matrix Collection. URL http://www.cise.ufl.edu/research/sparse/matrices/. 10.1145/2049662.2049663

2. Parallel Tridiagonal Equation Solvers

3. Merge Path - Parallel Merging Made Simple

4. R. W. Vuduc. Automatic Performance Tuning of Sparse Matrix Kernels. PhD thesis 2003. AAI3121741. R. W. Vuduc. Automatic Performance Tuning of Sparse Matrix Kernels . PhD thesis 2003. AAI3121741.

5. Optimization of sparse matrix-vector multiplication on emerging multicore platforms

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