A Data-Parallel ILUPACK for Sparse General and Symmetric Indefinite Linear Systems

DOI10.1007/978-3-319-58943-5_10zbMath1483.65049OpenAlexW2619241543MaRDI QIDQ5862560

Matthias Bollhöfer, Ernesto Dufrechou, Enrique S. Quintana-Ortí, Pablo Ezzatti, José I. Aliaga

Publication date: 9 March 2022

Published in: Euro-Par 2016: Parallel Processing Workshops (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-58943-5_10

zbMATH Keywords

preconditioningiterative solversgraphics processing unit (GPU)sparse triangular linear systemsincomplete LU (ILU) factorization

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Iterative numerical methods for linear systems (65F10) Parallel numerical computation (65Y05)

Uses Software

• CUDA
• CUSPARSE
• ILUPACK

Cites Work

• Exploiting thread-level parallelism in the iterative solution of sparse linear systems
• The university of Florida sparse matrix collection
• Inertia-Revealing Preconditioning For Large-Scale Nonconvex Constrained Optimization
• A Flexible Inner-Outer Preconditioned GMRES Algorithm
• Multilevel Preconditioners Constructed From Inverse-Based ILUs
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