Modeling and analyzing the energy consumption of fork‐join‐based task parallel programs
Modeling and analyzing the energy consumption of fork‐join‐based task parallel programs
复制标题
基于fork-join的任务并行程序的能耗建模与分析
DOI：
10.1002/cpe.3219
复制
发表时间：
2015
期刊：
影响因子：
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通讯作者：
G. Rünger
中科院分区：
文献类型：
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作者：
T. Rauber;G. Rünger
由于对环境和资金的关注，减少所有领域的能耗变得越来越重要，包括并行和高性能计算。在这篇文章中，我们提出了一种方法来减少执行一组以fork-join方式并行计算的任务所需的能耗。该方法包括一个分析模型的并行计算的能量消耗的分叉连接形式的动态电压频率缩放处理器，一个能量最佳的频率缩放状态的理论规范，和能量最小化通过计算最佳的比例因子。对于大量的任务，该方法是扩展的调度算法，利用分析结果，旨在减少能源。能源测量的复杂数值方法和SPEC CPU 2006基准以及大量的随机生成的任务的模拟说明和验证的能源建模，最小化和调度结果。版权所有© 2014约翰威利父子有限公司.
Because of environmental and monetary concerns, it is increasingly important to reduce the energy consumption in all areas, including parallel and high performance computing. In this article, we propose an approach to reduce the energy consumption needed for the execution of a set of tasks computed in parallel in a fork‐join fashion. The approach consists of an analytical model for the energy consumption of a parallel computation in fork‐join form on dynamic voltage frequency scaling processors, a theoretical specification of an energy‐optimal frequency‐scaled state, and the energy minimization by computing optimal scaling factors. For larger numbers of tasks, the approach is extended by scheduling algorithms, which exploit the analytical result and aim at a reduction of the energy. Energy measurements of a complex numerical method and the SPEC CPU2006 benchmarks as well as simulations for a large number of randomly generated tasks illustrate and validate the energy modeling, the minimization, and the scheduling results. Copyright © 2014 John Wiley & Sons, Ltd.
DOI：
10.1007/s10586-012-0211-1
发表时间：
2012-09
期刊：
Cluster Computing
影响因子：
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作者：
Jörg Dümmler;Raphael Kunis;G. Rünger
通讯作者：
Jörg Dümmler;Raphael Kunis;G. Rünger
DOI：
10.1002/cpe.1765
发表时间：
2011-10
期刊：
Concurrency and Computation: Practice and Experience
影响因子：
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作者：
Matthias Korch;T. Rauber;C. Scholtes
通讯作者：
Matthias Korch;T. Rauber;C. Scholtes