A CPU–GPU hybrid approach for the unsymmetric multifrontal method

Author:

Yu Chenhan D.,Wang Weichung,Pierce Dan’l

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Networks and Communications,Hardware and Architecture,Theoretical Computer Science,Software

Reference19 articles.

1. An unsymmetric-pattern multifrontal method for sparse lu factorization;Davis;SIAM Journal on Matrix Analysis and Applications,1997

2. A column pre-ordering strategy for the unsymmetric-pattern multifrontal method;Davis;ACM Transactions on Mathematical Software (TOMS),2004

3. Algorithm 832: UMFPACK V4. 3—an unsymmetric-pattern multifrontal method;Davis;ACM Transactions on Mathematical Software (TOMS),2004

4. WSMP: Watson Sparse Matrix Package, .

5. MUltifrontal Massively Parallel Solver Users’ guide, (2009).

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1. End-to-End LU Factorization of Large Matrices on GPUs;Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming;2023-02-21

2. Algorithmic Advancements and a Comparative Investigation of Left and Right Looking Sparse LU Factorization on GPU Platform for Circuit Simulation;IEEE Access;2022

3. GPU-Accelerated Adaptive PCBSO Mode-Based Hybrid RLA for Sparse LU Factorization in Circuit Simulation;IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems;2021-11

4. Design Considerations for GPU-based Mixed Integer Programming on Parallel Computing Platforms;50th International Conference on Parallel Processing Workshop;2021-08-09

5. GLU3.0: Fast GPU-based Parallel Sparse LU Factorization for Circuit Simulation;IEEE Design & Test;2020-06

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