Solving Linear Systems on a GPU with Hierarchically Off-Diagonal Low-Rank Approximations-Reference-Cited by-同舟云学术

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Solving Linear Systems on a GPU with Hierarchically Off-Diagonal Low-Rank Approximations

Published:2022-11 Issue: Volume: Page:
ISSN:
Container-title:SC22: International Conference for High Performance Computing, Networking, Storage and Analysis
language:
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Author:

Chen Chao¹,Martinsson Per-Gunnar²

Affiliation:

1. Oden Institute for Computational Engineering and Sciences, University of Texas at Austin,Austin,United States

2. Oden Institute for Computational Engineering and Sciences, University of Texas at Austin,Department of Mathematics,Austin,United States

Funder

Office of Naval Research

National Science Foundation

Department of Energy

ASCR

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10046045/10045783/10046094.pdf?arnumber=10046094

Reference63 articles.

1. Meeting the real-time challenges of ground-based telescopes using low-rank matrix computations

2. An Unsymmetric-Pattern Multifrontal Method for Sparse LU Factorization

3. A Fast Direct Solver for a Class of Elliptic Partial Differential Equations

4. A direct solver with O(N) complexity for integral equations on one-dimensional domains

5. Tile Low Rank Cholesky Factorization for Climate/Weather Modeling Applications on Manycore Architectures

Cited by 2 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. An O(N) distributed-memory parallel direct solver for planar integral equations;2024 IEEE International Parallel and Distributed Processing Symposium (IPDPS);2024-05-27

2. An inherently parallel ℋ²-ULV factorization for solving dense linear systems on GPUs;The International Journal of High Performance Computing Applications;2024-04-03

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