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Fine-grained bit-flip protection for relaxation methods
dc.contributor.author | Anzt, Hartwig | |
dc.contributor.author | Dongarra, Jack | |
dc.contributor.author | Quintana-Ortí, Gregorio | |
dc.date.accessioned | 2019-11-26T12:18:55Z | |
dc.date.available | 2019-11-26T12:18:55Z | |
dc.date.issued | 2019-09 | |
dc.identifier.uri | http://hdl.handle.net/10234/185208 | |
dc.description.abstract | Resilience is considered a challenging under-addressed issue that the high performance computing community (HPC) will have to face in order to produce reliable Exascale systems by the beginning of the next decade. As part of a push toward a resilient HPC ecosystem, in this paper we propose an error-resilient iterative solver for sparse linear systems based on stationary component-wise relaxation methods. Starting from a plain implementation of the Jacobi iteration, our approach introduces a low-cost component-wise technique that detects bit-flips, rejecting some component updates, and turning the initial synchronized solver into an asynchronous iteration. Our experimental study with sparse incomplete factorizations from a collection of real-world applications, and a practical GPU implementation, exposes the convergence delay incurred by the fault-tolerant implementation and its practical performance. | ca_CA |
dc.format.extent | 11 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Elsevier | ca_CA |
dc.rights | © 2016 Elsevier B.V. All rights reserved. | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | * |
dc.subject | sparse linear systems | ca_CA |
dc.subject | iterative solvers | ca_CA |
dc.subject | Jacobi method | ca_CA |
dc.subject | fault tolerance | ca_CA |
dc.subject | bit flips | ca_CA |
dc.subject | high performance computing | ca_CA |
dc.title | Fine-grained bit-flip protection for relaxation methods | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1016/j.jocs.2016.11.013 | |
dc.relation.projectID | U.S. Department of Energy (Award Number DE-SC-0010042) and NVIDIA ; MINECO and FEDER (project CICYT TIN2014-53495-R). | ca_CA |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | https://www.sciencedirect.com/science/article/pii/S1877750316303891 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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