Taking advantage of GPU/CPU architectures for sparse Conjugate Gradient solver computation

TitreTaking advantage of GPU/CPU architectures for sparse Conjugate Gradient solver computation
Publication TypeConference Paper
Year of Publication2015
AuthorsKasmi, Na, Zbakh, Ma, Mahmoudi, SAb, Manneback, Pb
Conference NameProceedings of 2015 IEEE World Conference on Complex Systems, WCCS 2015
Abstract

Solving large sparse linear systems is a time and energy consuming process. This paper presents an efficient exploitation of graphic processing units (GPUs) for accelerating Conjugate Gradient iterative solver (CG). We use the high-level software library PARALUTION for sparse linear algebra on multi/many-core systems, which supports GPU (with CUDA and OpenCL) and Multi-CPU implementations of CG method using different storage formats. We discuss and compare performance using three platforms. © 2015 IEEE.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84978427957&doi=10.1109%2fICoCS.2015.7483268&partnerID=40&md5=af973d4adddb0778d096c29e4a71e051
DOI10.1109/ICoCS.2015.7483268
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