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The emergence and continuing use of multi-core architectures require changes in the existing software and sometimes even a redesign of the established algorithms in order to take advantage of now prevailing parallelism. The Parallel Linear Algebra for Scalable Multi-core Architectures (PLASMA) is a project that aims to achieve both high performance and portability across a wide range of multi-core architectures. We present in this paper a comparative study of PLASMA's performance against established linear algebra packages (LAPACK and ScaLAPACK), against new approaches at parallel execution (Task Based Linear Algebra Subroutines -- TBLAS), and against equivalent commercial software offerings (MKL, ESSL and PESSL). Our experiments were conducted on one-sided linear algebra factorizations (LU, QR and Cholesky) and used multi-core architectures (based on Intel Xeon EMT64 and IBM Power6). A performance improvement of 67% was for instance obtained on the Cholesky factorization of a matrix of order 4000, using 32 cores.
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Emmanuel Agullo
Institut national de recherche en sciences et technologies du numérique
Bilel Hadri
King Abdullah University of Science and Technology
Hatem Ltaief
Beijing Institute of Technology
University of Tennessee at Knoxville
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Agullo et al. (Sat,) studied this question.
synapsesocial.com/papers/6a2171b6582b7ad9ebabb2a9 — DOI: https://doi.org/10.1145/1654059.1654080
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