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Maximizing reliability with energy conservation for parallel task scheduling in a heterogeneous cluster

机译:通过节能最大化可靠性,以实现异构集群中的并行任务调度

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摘要

A heterogeneous computing system in a cluster is a promising computing platform, which attracts a large number of researchers due to its high performance potential. High system reliability and low power consumption are two primary objectives for a data center. Dynamic voltage scaling (DVS) has been proved to be the most efficient technique and is exploited widely to realize a low power system. Unfortunately, transient fault is inevitable during the execution of an application while applying the DVS technique. Most existing scheduling algorithms for precedence constrained tasks in a multiprocessor computer system do not adequately consider task reliability. In this paper, we devise a novel Reliability Maximization with Energy Constraint (RMEC) algorithm, which incorporates three important phases, including task priority establishment, frequency selection, and processor assignment. The RMEC algorithm can effectively balance the tradeoff between high reliability and energy consumption. Our rigorous performance evaluation study, based on both randomly generated task graphs and the graphs of some real-world applications, shows that our scheduling algorithm surpasses the existing algorithms in terms of system reliability enhancement and energy consumption saving. (C) 2015 Elsevier Inc. All rights reserved.
机译:集群中的异构计算系统是一个很有前途的计算平台,由于其高性能潜力而吸引了大量研究人员。高系统可靠性和低功耗是数据中心的两个主要目标。动态电压缩放(DVS)已被证明是最有效的技术,已被广泛用于实现低功耗系统。不幸的是,在应用DVS技术的同时,在执行应用程序期间不可避免地会出现瞬时故障。在多处理器计算机系统中,大多数现有的优先级受限任务调度算法都没有充分考虑任务可靠性。在本文中,我们设计了一种新的具有能量约束的可靠性最大化(RMEC)算法,该算法包含三个重要阶段,包括任务优先级建立,频率选择和处理器分配。 RMEC算法可以有效地平衡高可靠性和能耗之间的折衷。我们基于随机生成的任务图和一些实际应用的图进行的严格性能评估研究表明,在系统可靠性增强和节能方面,我们的调度算法优于现有算法。 (C)2015 Elsevier Inc.保留所有权利。

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