Adaptive Precision Sparse Matrix–Vector Product and Its Application to Krylov Solvers-Reference-Cited by-同舟云学术

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Adaptive Precision Sparse Matrix–Vector Product and Its Application to Krylov Solvers

Published:2024-01-25 Issue:1 Volume:46 Page:C30-C56
ISSN:1064-8275
Container-title:SIAM Journal on Scientific Computing
language:en
Short-container-title:SIAM J. Sci. Comput.

Author:

Graillat Stef¹,Jézéquel Fabienne²,Mary Theo¹,Molina Roméo³

Affiliation:

1. Sorbonne Université, CNRS, LIP6, Paris, F-75005, France.

2. Sorbonne Université, CNRS, LIP6, Paris, F-75005, France, and Université Paris-Panthéon-Assas, Paris, F-75006, France.

3. Sorbonne Université, CNRS, LIP6, and Université Paris-Saclay, Paris, F-75005, France.

Funder

Agence Nationale de la Recherche

Centre National de la Recherche Scientifique

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Reference26 articles.

1. Data-driven Mixed Precision Sparse Matrix Vector Multiplication for GPUs

2. Compressed basis GMRES on high-performance graphics processing units

3. Mixed precision low-rank approximations and their application to block low-rank LU factorization

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reduced-Precision and Reduced-Exponent Formats for Accelerating Adaptive Precision Sparse Matrix–Vector Product;Lecture Notes in Computer Science;2024

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