Linear Systems Solvers for Distributed-Memory Machines with GPU Accelerators

DOI10.1007/978-3-030-29400-7_35zbMath1452.65002OpenAlexW2968304367MaRDI QIDQ3297578

Asim Yarkhan, Ali Charara, Ichitaro Yamazaki, Mark Ralph Gates, Jakub Kurzak, Jack J. Dongarra

Publication date: 20 July 2020

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-030-29400-7_35

zbMATH Keywords

Cholesky factorizationLU factorizationlinear algebraGPU accelerationdistributed memorylinear systems of equations

Mathematics Subject Classification ID

Parallel numerical computation (65Y05) Direct numerical methods for linear systems and matrix inversion (65F05) Numerical algorithms for specific classes of architectures (65Y10) Software, source code, etc. for problems pertaining to numerical analysis (65-04)

Uses Software

• LAPACK
• ScaLAPACK
• Slate

Cites Work

• Unnamed Item
• Parallel and Cache-Efficient In-Place Matrix Storage Format Conversion
• Scaling LAPACK panel operations using parallel cache assignment
• ScaLAPACK Users' Guide
• A High Performance QDWH-SVD Solver Using Hardware Accelerators
• A recursive formulation of Cholesky factorization of a matrix in packed storage

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