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Maximizing reliability of energy constrained parallel applications on heterogeneous distributed systems

机译:最大化异构分布式系统上受能量限制的并行应用程序的可靠性

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Energy is one of the primary design constraints in heterogeneous distributed systems ranging from small embedded devices to large-scale data centers, where a parallel application with precedence-constrained tasks is represented by a directed acyclic graph (DAG). Dynamic voltage and frequency scaling (DVFS) has become an important energy control technology by simultaneously scaling down processor's supply voltage and frequency while tasks are running. However, recent studies show that dynamically scaling down the chip's voltage may lead to a sharp rise in transient failures of processors, thereby affecting the reliability of the system. This study solves the problem of maximizing reliability of an energy constrained parallel application on heterogeneous distributed systems based on DVFS. The problem is decomposed into two sub -problems, namely, satisfying energy constraint and maximizing reliability. The first sub-problem is solved by transferring the energy constraint of the application to that of each task, and the second subproblem is solved by heuristically scheduling each task with maximum reliability value while satisfying its energy constraint. Experiments with real parallel applications show that the proposed MREC algorithm can obtain larger reliability values than the state-of-the-art reliability maximum energy conservation (RMEC) algorithm while satisfying the energy constraints. (C) 2017 Elsevier B.V. All rights reserved.
机译:能源是从小型嵌入式设备到大型数据中心的异构分布式系统中的主要设计约束之一,在分布式分布式系统中,具有优先级受限任务的并行应用程序由有向无环图(DAG)表示。动态电压和频率缩放(DVFS)通过在任务运行时同时缩小处理器的电源电压和频率,已成为一种重要的能量控制技术。但是,最近的研究表明,动态缩小芯片电压可能会导致处理器瞬态故障的急剧增加,从而影响系统的可靠性。本研究解决了基于DVFS的异构分布式系统上能量受限并行应用的最大可靠性问题。该问题被分解为两个子问题,即满足能量约束和最大化可靠性。通过将应用程序的能量约束转移到每个任务的能量约束来解决第一个子问题,并通过在满足其能量约束的同时以最大的可靠性值试探性地调度每个任务来解决第二个子问题。实际并行应用程序的实验表明,与现有技术的最大可靠性最大节能(RMEC)算法相比,所提出的MREC算法可以获得更大的可靠性值,同时又满足了能量约束。 (C)2017 Elsevier B.V.保留所有权利。

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