A Case Study on Modeling the Performance of Dense Matrix Computation: Tridiagonalization in the EigenExa Eigensolver on the K Computer-Reference-Cited by-同舟云学术

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A Case Study on Modeling the Performance of Dense Matrix Computation: Tridiagonalization in the EigenExa Eigensolver on the K Computer

Published:2018-05 Issue: Volume: Page:
ISSN:
Container-title:2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW)
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Author:

Fukaya Takeshi,Imamura Toshiyuki,Yamamoto Yusaku

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8424927/8425307/08425538.pdf?arnumber=8425538

Cited by 4 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. ChASE;Proceedings of the Platform for Advanced Scientific Computing Conference;2022-06-27

2. Algorithm 1019: A Task-based Multi-shift QR/QZ Algorithm with Aggressive Early Deflation;ACM Transactions on Mathematical Software;2022-03-31

3. Performance prediction of massively parallel computation by Bayesian inference;JSIAM Letters;2022

4. EigenKernel;Japan Journal of Industrial and Applied Mathematics;2019-04-29

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