Generating Approximate Inverse Preconditioners for Sparse Matrices Using CUDA and GPGPU

DOI10.1260/1748-3018.5.3.475zbMath1229.65059OpenAlexW2089510446MaRDI QIDQ3100112

No author found.

Publication date: 22 November 2011

Published in: Journal of Algorithms & Computational Technology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1260/1748-3018.5.3.475

zbMATH Keywords

complexityalgorithmspreconditioningparallel computationGMRESsparse matricesKrylov subspace methodCUDA

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Iterative numerical methods for linear systems (65F10) Parallel numerical computation (65Y05) Complexity and performance of numerical algorithms (65Y20) Packaged methods for numerical algorithms (65Y15) Preconditioners for iterative methods (65F08)

Related Items (1)

Sparse approximate inverse preconditioners on high performance GPU platforms

This page was built for publication: Generating Approximate Inverse Preconditioners for Sparse Matrices Using CUDA and GPGPU