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首页> 外文期刊>International Journal of Combinatorial Optimization Problems and Informatics >Energy-Aware Scheduler for HPC Parallel Task Base Applications in Cloud Computing
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Energy-Aware Scheduler for HPC Parallel Task Base Applications in Cloud Computing

机译：面向云计算中HPC并行任务库应用程序的能源感知调度程序

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摘要

In the world, distributed platforms such as clusters, grids, and clouds spend around 1.5%-2.0% of the total energy consumption and this demand is growing extremely fast. For reducing energy consumption one of the methods is providing scheduling policies in order to allocate tasks on specific resources that impact over the processing times and energy consumption. In this paper, we propose a scheduling system to execute efficiently task-based applications on distributed computing platforms in order to minimize the energy consumption, execution time or both, also we present a dynamic online polynomial-time algorithm that combines a set of heuristic rules and a resource allocation technique in order to get good solutions on an affordable time scale. A prototype implementation of the scheduler has been tested with matrix multiplication DAG generated at random as well as on real task-based COMPSs applications, concluding that our method is suitable for run-time scheduling.
机译：在世界范围内，诸如群集，网格和云之类的分布式平台花费了总能耗的大约1.5％-2.0％，并且这种需求正在以极快的速度增长。为了减少能耗，一种方法是提供调度策略，以便在影响处理时间和能耗的特定资源上分配任务。在本文中，我们提出了一种调度系统，以在分布式计算平台上高效执行基于任务的应用程序，以最大程度地减少能耗和/或执行时间，同时，我们提出了一种动态的在线多项式时间算法，该算法结合了一组启发式规则以及资源分配技术，以便在可承受的时间范围内获得良好的解决方案。调度程序的原型实现已通过随机生成的矩阵乘法DAG以及基于实际任务的COMPSs应用程序进行了测试，结论是我们的方法适用于运行时调度。

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