Parallelization using task parallel library with task-based programming model

In order to reduce the complexity of traditional multithreaded parallel programming, this paper explores a new task-based parallel programming using the Microsoft .NET Task Parallel Library (TPL). Firstly, this paper proposes a custom data partitioning optimization method to achieve an efficient dat...

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Vydáno v:Proceedings (IEEE International Conference on Software Engineering and Service Sciences. Print) s. 653 - 656
Hlavní autoři: Xinhong Hei, Jinlong Zhang, Bin Wang, Haiyan Jin, Giacaman, Nasser
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2014
Témata:
Computational modeling
Data models
Data parallelism
Educational institutions
Instruction sets
Parallel processing
Parallel programming
Task parallelism
Task-based
TPL
ISBN:1479932787, 9781479932788
ISSN:2327-0586
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Shrnutí:In order to reduce the complexity of traditional multithreaded parallel programming, this paper explores a new task-based parallel programming using the Microsoft .NET Task Parallel Library (TPL). Firstly, this paper proposes a custom data partitioning optimization method to achieve an efficient data parallelism, and applies it to the matrix multiplication. The result of the application supports the custom data partitioning optimization method. Then we develop a task parallel application: Image Blender, and this application explains the efficiency and pitfall aspects associated with task parallelism. Finally, the paper analyzes the performance of our applications. Experiments results show that TPL can dramatically alleviate programmer burden and boost the performance of programs with its task-based parallel programming mechanism.
ISBN:1479932787
9781479932788
ISSN:2327-0586
DOI:10.1109/ICSESS.2014.6933653