A Bi-objective Optimization Framework for Heterogeneous CPU/GPU Query Plans
Krzysztof Kaczmarski , Piotr Przymus , Krzysztof Stencel
AbstractGraphics 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.
|Publication size in sheets||0.6|
Szczuka Marcin, Czaja Ludwik , Kacprzak Magdalena (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, ISBN 978-83-62582-42-6, 489 p.
frontmatter-1.pdf / 78.02 KB / No licence information
|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.|
|Score|| = 10.0, 17-02-2020, BookChapterSeriesAndMatConfByIndicator|
= 15.0, 17-02-2020, BookChapterSeriesAndMatConfByIndicator
|Publication indicators||= 0|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.