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URN: urn:nbn:de:swb:90-295264

A Block-Asynchronous Relaxation Method for Graphics Processing Units

Anzt, H.; Dongarra, J.; Heuveline, Vincent; Tomov, S.

In this paper, we analyze the potential of asynchronous relaxation methods on Graphics Processing Units (GPUs). For this purpose, we developed a set of asynchronous iteration algorithms in CUDA and compared them with a parallel implementation of synchronous relaxation methods on CPU-based systems. For a set of test matrices taken from the University of Florida Matrix Collection we monitor the convergence behavior, the average iteration time and the total time-to-solution time. Analyzing the results, we observe that even for our most basic asynchronous relaxation scheme, despite its lower convergence rate compared to the Gauss-Seidel relaxation (that we expected), the asynchronous iteration running on GPUs is still able to provide solution approximations of certain accuracy in considerably shorter time than Gauss-Seidel running on CPUs. Hence, it overcompensates for the slower convergence by exploiting the scalability and the good fit of the asynchronous schemes for the highly parallel GPU architectures. Further, enhancing the most basic asynchronous approach with hybrid schemes -- using multiple iterations within the "subdomain ... mehr

Zugehörige Institution(en) am KIT Institut für Angewandte und Numerische Mathematik (IANM)
Publikationstyp Forschungsbericht
Jahr 2011
Sprache Englisch
Identifikator ISSN: 2191-0693
KITopen ID: 1000029526
Verlag KIT, Karlsruhe
Serie Preprint Series of the Engineering Mathematics and Computing Lab (EMCL) ; 2011,14
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