EAD and PEBD: Two Energy-Aware Duplication Scheduling Algorithms for Parallel Tasks on Homogeneous Clusters
EAD and PEBD: Two Energy-Aware Duplication Scheduling Algorithms for Parallel Tasks on Homogeneous Clusters
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DOI：
10.1109/tc.2010.216
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发表时间：
2011-03-01
影响因子：
3.7
通讯作者：
Qin, Xiao
中科院分区：
文献类型：
--
作者：
Zong, Ziliang;Manzanares, Adam;Qin, Xiao
高性能集群已被广泛部署，以解决具有挑战性和严格的科学和工程任务。一方面，在设计运行并行应用程序的集群时，高性能当然是一个重要的考虑因素。另一方面，不断增长的能源成本要求我们在集群中有效地节约能源。为了实现集群性能和能量效率的双重优化，本文提出了两种基于副本的节能调度算法--能量感知副本调度（EAD）和性能能量平衡副本调度（PEBD）。现有的基于复制的调度算法复制所有可能的任务来缩短调度长度，但没有减少由复制引起的能量消耗。相比之下，我们的算法，努力平衡时间表的长度和节能明智地复制的任务的前辈，如果重复可以帮助在性能而不降低能源效率。为了说明EAD和PEBD的有效性，我们将它们与非重复算法，传统的基于重复的算法和动态电压缩放（DVS）算法进行比较。大量的实验结果使用合成基准和现实世界的应用程序表明，我们的算法可以有效地节省能源与边际性能下降。
High-performance clusters have been widely deployed to solve challenging and rigorous scientific and engineering tasks. On one hand, high performance is certainly an important consideration in designing clusters to run parallel applications. On the other hand, the ever increasing energy cost requires us to effectively conserve energy in clusters. To achieve the goal of optimizing both performance and energy efficiency in clusters, in this paper, we propose two energy-efficient duplication-based scheduling algorithms-Energy-Aware Duplication (EAD) scheduling and Performance-Energy Balanced Duplication (PEBD) scheduling. Existing duplication-based scheduling algorithms replicate all possible tasks to shorten schedule length without reducing energy consumption caused by duplication. Our algorithms, in contrast, strive to balance schedule lengths and energy savings by judiciously replicating predecessors of a task if the duplication can aid in performance without degrading energy efficiency. To illustrate the effectiveness of EAD and PEBD, we compare them with a nonduplication algorithm, a traditional duplication-based algorithm, and the dynamic voltage scaling (DVS) algorithm. Extensive experimental results using both synthetic benchmarks and real-world applications demonstrate that our algorithms can effectively save energy with marginal performance degradation.