Communication in task-parallel ILU-preconditioned CG solversusing MPI + OmpSs
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Other documents of the author: Aliaga Estellés, José Ignacio; Barreda Vayá, Maria; Flegar, Goran; Bollhöffer, Matthias; Quintana-Orti, Enrique S.
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7036
comunitat-uji-handle3:10234/8620
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Title
Communication in task-parallel ILU-preconditioned CG solversusing MPI + OmpSsAuthor (s)
Date
2017-11-10Publisher
WileyISSN
1532-0626; 1532-0634Bibliographic citation
ALIAGA, José I., et al. Communication in task‐parallel ILU‐preconditioned CG solvers using MPI+ OmpSs. Concurrency and Computation: Practice and Experience, 2017, vol. 29, no 21.Type
info:eu-repo/semantics/articlePublisher version
Concurrency and Computation: Practice and Experience, 2017, vol. 29, no 21Version
info:eu-repo/semantics/acceptedVersionSubject
Abstract
We target the parallel solution of sparse linear systems via iterative Krylov subspace–based methods enhanced with incomplete LU (ILU)-type preconditioners on clusters of multicore processors. In order to tackle ... [+]
We target the parallel solution of sparse linear systems via iterative Krylov subspace–based methods enhanced with incomplete LU (ILU)-type preconditioners on clusters of multicore processors. In order to tackle large-scale problems, we develop task-parallel implementations of the classical iteration for the CG method, accelerated via ILUPACK and ILU(0) preconditioners, using MPI + OmpSs. In addition, we integrate several communication-avoiding strategies into the codes, including the butterfly communication scheme and Eijkhout's formulation of the CG method. For all these implementations, we analyze the communication patterns and perform a comparative analysis of their performance and scalability on a cluster consisting of 16 nodes, with 16 cores each. [-]
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