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Titlebook: High Performance Computing for Computational Science -- VECPAR 2014; 11th International C Michel Daydé,Osni Marques,Kengo Nakajima Conferen

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发表于 2025-3-21 16:29:41 | 显示全部楼层 |阅读模式
书目名称High Performance Computing for Computational Science -- VECPAR 2014
副标题11th International C
编辑Michel Daydé,Osni Marques,Kengo Nakajima
视频video
概述Includes supplementary material:
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: High Performance Computing for Computational Science -- VECPAR 2014; 11th International C Michel Daydé,Osni Marques,Kengo Nakajima Conferen
描述.This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on High Performance Computing for Computational Science, VECPAR 2014, held in Eugene, OR, USA, in June/July 2014. .The 25 papers presented were carefully reviewed and selected of numerous submissions. The papers are organized in topical sections on algorithms for GPU and manycores, large-scale applications, numerical algorithms, direct/hybrid methods for solving sparse matrices, performance tuning. The volume also contains the papers presented at the 9th International Workshop on Automatic Performance Tuning..
出版日期Conference proceedings 2015
关键词code generation; computations on matrices; computing methodologies; data intensive computing; distribute
版次1
doihttps://doi.org/10.1007/978-3-319-17353-5
isbn_softcover978-3-319-17352-8
isbn_ebook978-3-319-17353-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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发表于 2025-3-21 21:26:22 | 显示全部楼层
Conference proceedings 2015submissions. The papers are organized in topical sections on algorithms for GPU and manycores, large-scale applications, numerical algorithms, direct/hybrid methods for solving sparse matrices, performance tuning. The volume also contains the papers presented at the 9th International Workshop on Automatic Performance Tuning..
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Using Random Butterfly Transformations to Avoid Pivoting in Sparse Direct Methodsithout pivoting with probability one. This approach has been successful for dense matrices; in this work, we investigate the sparse case. In particular, we address the issue of fill-in in the transformed system.
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