A Bi-objective Optimization Framework for Heterogeneous CPU/GPU Query Plans
- Krzysztof Kaczmarski,
- Piotr Przymus,
- Krzysztof Stencel
Graphics Processing Units (GPU) have significantly more applications than just rendering images. They are also used in generalpurpose computing to solve problems that can benefit from massive parallel processing. However, there are tasks that either hardly suit GPU or fit GPU only partially. The latter class is the focus of this paper. We elaborate on hybrid CPU/GPU computation and build optimisation methods that seek the equilibrium between these two computation platforms. The method is based on heuristic search for bi-objective Pareto optimal execution plans in presence of multiple concurrent queries. The underlying model mimics the commodity market where devices are producers and queries are consumers. The value of resources of computing devices is controlled by supply-and-demand laws. Our model of the optimization criteria allows finding solutions of problems not yet addressed in heterogeneous query processing. Furthermore, it also offers lower time complexity and higher accuracy than other methods.
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- Szczuka Marcin, Marcin Szczuka Czaja Ludwik , Ludwik Czaja Kacprzak Magdalena Magdalena Kacprzak (eds.): Proceedings of the 22nd International Workshop on Concurrency, Specification and Programming (CS&P 2013), CEUR Workshop Proceedings, vol. 1032, 2013, Aachen University, Germany, CEUR-WS, 489 p., ISBN 978-83-62582-42-6
- Abstract in Polish
- Opracowano nowy sposób planowania optymalnego wykonania zapytań do baz danych w heterogenicznych środowiskach zbudowany na wycenie ekonomicznej zasobów oraz dwucelowej optymalizacji Pareto.
- http://ceur-ws.org/Vol-1032/ Opening in a new tab
- (en) English
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