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A mixed-precision algorithm for the solution of Lyapunov equations on hybrid CPU–GPU platforms
dc.contributor.author | Benner, Peter | |
dc.contributor.author | Ezzatti, Pablo | |
dc.contributor.author | Kressner, Daniel | |
dc.contributor.author | Quintana-Orti, Enrique S. | |
dc.contributor.author | Remón Gómez, Alfredo | |
dc.date.accessioned | 2012-09-12T11:06:32Z | |
dc.date.available | 2012-09-12T11:06:32Z | |
dc.date.issued | 2011 | |
dc.identifier.citation | Parallel Computing (Aug. 2011) vol. 37, no. 8, p. 439-450 | |
dc.identifier.issn | 0167-8191 | |
dc.identifier.uri | http://hdl.handle.net/10234/46895 | |
dc.description.abstract | We describe a hybrid Lyapunov solver based on the matrix sign function, where the intensive parts of the computation are accelerated using a graphics processor (GPU) while executing the remaining operations on a general-purpose multi-core processor (CPU). The initial stage of the iteration operates in single-precision arithmetic, returning a low-rank factor of an approximate solution. As the main computation in this stage consists of explicit matrix inversions, we propose a hybrid implementation of Gauß–Jordan elimination using look-ahead to overlap computations on GPU and CPU. To improve the approximate solution, we introduce an iterative refinement procedure that allows to cheaply recover full double-precision accuracy. In contrast to earlier approaches to iterative refinement for Lyapunov equations, this approach retains the low-rank factorization structure of the approximate solution. The combination of the two stages results in amixed-precision algorithm, that exploits the capabilities of both general-purpose CPUs and many-core GPUs and overlaps critical computations. Numerical experiments using real-world data and a platform equipped with two Intel Xeon QuadCore processors and an Nvidia Tesla C1060 show a significant efficiency gain of the hybrid method compared to a classical CPU implementation. | ca_CA |
dc.format.extent | 12 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language | eng | ca_CA |
dc.language.iso | cat | ca_CA |
dc.publisher | Elsevier | ca_CA |
dc.rights | © 2011 Elsevier Inc. All rights reserved | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | * |
dc.subject | Lyapunov equations | ca_CA |
dc.subject | Matrix sign function | ca_CA |
dc.subject | Iterative refinement | ca_CA |
dc.subject | Graphics processors | ca_CA |
dc.subject | Multi-core processors | ca_CA |
dc.subject | Model reduction | ca_CA |
dc.title | A mixed-precision algorithm for the solution of Lyapunov equations on hybrid CPU–GPU platforms | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | http://dx.doi.org/10.1016/j.parco.2010.12.002 | |
dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | ca_CA |
dc.relation.publisherVersion | http://www.sciencedirect.com/science/article/pii/S0167819110001560 | ca_CA |
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