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Programming support and scheduling for communicating parallel tasks

delete2013-02-01
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PRE
AI
J
Jörg Dümmler *
T
Thomas Rauber
G
Gudula Rünger
DOI:10.1016/j.jpdc.2012.09.017delete
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Abstract

Abstract

En 中文
Task-based programming models are beneficial for the development of parallel programs for several reasons. They provide a decoupling of the specification of parallelism from the scheduling and mapping to execution resources of a specific hardware platform, thus allowing a flexible and individual mapping. For platforms with a distributed address space, the use of parallel tasks, instead of sequential tasks, adds the additional advantage of a structuring of the program into communication domains that can help to reduce the overall communication overhead. In this article, we consider the parallel programming model of communicating parallel tasks (CM-tasks), which allows both task-internal communication as well as communication between concurrently executed tasks at arbitrary points of their execution. We propose a corresponding scheduling algorithm and describe how the scheduling is supported by a transformation tool. An experimental evaluation using synthetic task graphs as well as several complex application programs shows that employing the CM-task model may lead to significant performance improvements compared to other parallel execution schemes. (C) 2012 Elsevier Inc. All rights reserved.
Keywords:
Parallel tasks
Scheduling
Mixed parallelism
Algorithms
Scalability
Tool support

Journal

Journal of Parallel and Distributed Computing cover
Journal of Parallel and Distributed Computing
IF:
4
Papers:
3.8K
Citations:
4.8K

Organization

U
University of Bayreuth
Scholars:
7.4K
Papers: 6.7K
Citations: 1.2W
T
Technische Universitat Chemnitz
Scholars:
3.3K
Papers: 2.8K
Citations: 23
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