Unified Communication Optimization Strategies for Sparse Triangular Solver on CPU and GPU Clusters-Reference-Cited by-同舟云学术

Unified Communication Optimization Strategies for Sparse Triangular Solver on CPU and GPU Clusters

Published:2023-11-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
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Author:

Liu Yang¹^ORCID,Ding Nan¹^ORCID,Sao Piyush²^ORCID,Williams Samuel¹^ORCID,Li Xiaoye Sherry¹^ORCID

Affiliation:

1. Lawrence Berkeley National Laboratory, Berkeley, United States of America

2. Oak Ridge National Laboratory, Oak Ridge, United States of America

Funder

Scientific Discovery through Advanced Computing (SciDAC) program through the FASTMath Institute

Exascale Computing Project

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581784.3607092

Reference45 articles.

1. A Prediction Framework for Fast Sparse Triangular Solves

2. A Hybrid Multithreaded Direct Sparse Triangular Solver

3. The university of Florida sparse matrix collection

4. James Demmel , Laura Grigori , Mark Hoemmen , and Julien Langou . 2008. Communication-avoiding parallel and sequential QR factorizations. CoRR abs/0806.2159 ( 2008 ). James Demmel, Laura Grigori, Mark Hoemmen, and Julien Langou. 2008. Communication-avoiding parallel and sequential QR factorizations. CoRR abs/0806.2159 (2008).

5. Avoiding communication in sparse matrix computations

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