Detailed Information on Publication Record
2011
Computing Optimal Cycle Mean in Parallel on CUDA
BARNAT, Jiří, Petr BAUCH, Luboš BRIM and Milan ČEŠKABasic information
Original name
Computing Optimal Cycle Mean in Parallel on CUDA
Name in Czech
Paralelní CUDA algoritmy pro výpočet cyklů s optimální hodnotou
Authors
BARNAT, Jiří (203 Czech Republic, guarantor, belonging to the institution), Petr BAUCH (203 Czech Republic, belonging to the institution), Luboš BRIM (203 Czech Republic, belonging to the institution) and Milan ČEŠKA (203 Czech Republic, belonging to the institution)
Edition
Electronic Proceedings in Theoretical Computer Science, 2011, 2075-2180
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
United States of America
Confidentiality degree
není předmětem státního či obchodního tajemství
References:
RIV identification code
RIV/00216224:14330/11:00050202
Organization unit
Faculty of Informatics
UT WoS
000219679600009
Keywords (in Czech)
Ověřování modelu; hardvérové platformy; paralelismus
Keywords in English
Model checking; hardware platforms; parallelism
Tags
International impact, Reviewed
Změněno: 12/12/2012 11:09, Mgr. Petr Bauch, Ph.D.
V originále
Computation of optimal cycle mean in a directed weighted graph has many applications in program analysis, performance verification in particular. In this paper we propose a data-parallel algorithmic solution to the problem and show how the computation of optimal cycle mean can be efficiently accelerated by means of CUDA technology. We show how the problem of computation of optimal cycle mean is decomposed into a sequence of data-parallel graph computation primitives and show how these primitives can be implemented and optimized for CUDA computation. Finally, we report a fivefold experimental speed up on graphs representing models of distributed systems when compared to best sequential algorithms.
In Czech
Výpočet cyklů s optimální hodnotou v orientovaném grafu má mnoho různých využití. V tomto článku navrhujeme nový datově paralelní algoritmus pro řešení prolému s využitím technologie CUDA. Experimentální měření ukazují až pětinásobné zrychlení v porovnání s nejlepším sekvenčním algoritmem.
Links
GA201/09/1389, research and development project |
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GD102/09/H042, research and development project |
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GP201/09/P497, research and development project |
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MSM0021622419, plan (intention) |
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MUNI/A/0914/2009, interní kód MU |
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