Accelerating the reduction to upper Hessenberg, tridiagonal, and bidiagonal forms through hybrid GPU-based computing

We present a Hessenberg reduction (HR) algorithm for hybrid systems of homogeneous multicore with GPU accelerators that can exceed 25× the performance of the corresponding LAPACK algorithm running on current homogeneous multicores. This enormous acceleration is due to proper matching of algorithmic...

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Veröffentlicht in:	Parallel computing Jg. 36; H. 12; S. 645 - 654
Hauptverfasser:	Tomov, Stanimire, Nath, Rajib, Dongarra, Jack
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2010
Schlagworte:	Accelerators Algorithms Bidiagonalization Computation Computer programs Dense linear algebra Eigenvalues GPUs Hessenberg reduction Hybrid computing Hybrid systems Reduction Running Tridiagonalization Two-sided factorizations Hybrid computing Bidiagonalization GPUs Tridiagonalization Two-sided factorizations Hessenberg reduction Dense linear algebra
ISSN:	0167-8191, 1872-7336
Online-Zugang:	Volltext
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