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A high performance algorithm for static task scheduling in heterogeneous distributed computing systems

机译:异构分布式计算系统中用于静态任务调度的高性能算法

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Effective task scheduling is essential for obtaining high performance in heterogeneous distributed computing systems (HeDCSs). However, finding an effective task schedule in HeDCSs requires the consideration of both the heterogeneity of processors and high interprocessor communication overhead, which results from non-trivial data movement between tasks scheduled on different processors. In this paper, we present a new high-performance scheduling algorithm, called the longest dynamic critical path (LDCP) algorithm, for HeDCSs with a bounded number of processors. The LDCP algorithm is a list-based scheduling algorithm that uses a new attribute to efficiently select tasks for scheduling in HeDCSs. The efficient selection of tasks enables the LDCP algorithm to generate high-quality task schedules in a heterogeneous computing environment. The performance of the LDCP algorithm is compared to two of the best existing scheduling algorithms for HeDCSs: the HEFT and DLS algorithms. The comparison study shows that the LDCP algorithm outperforms the HEFT and DLS algorithms in terms of schedule length and speedup. Moreover, the improvement in performance obtained by the LDCP algorithm over the HEFT and DLS algorithms increases as the inter-task communication cost increases. Therefore, the LDCP algorithm provides a practical solution for scheduling parallel applications with high communication costs in HeDCSs.
机译:有效的任务调度对于在异构分布式计算系统(HeDCS)中获得高性能至关重要。但是,在HeDCS中找到有效的任务计划需要同时考虑处理器的异构性和高的处理器间通信开销,这是由在不同处理器上计划的任务之间的非平凡数据移动造成的。在本文中,我们为处理器数量有限的HeDCS提出了一种新的高性能调度算法,称为最长动态关键路径(LDCP)算法。 LDCP算法是基于列表的调度算法,它使用新属性来有效选择任务以在HeDCS中进行调度。任务的有效选择使LDCP算法能够在异构计算环境中生成高质量的任务计划。 LDCP算法的性能与HeDCS的两种最佳现有调度算法进行了比较:HEFT和DLS算法。比较研究表明,在调度长度和加速方面,LDCP算法优于HEFT和DLS算法。此外,随着任务间通信成本的增加,通过LDCP算法获得的性能优于HEFT和DLS算法的提高也有所增加。因此,LDCP算法为HeDCS中通信成本高的并行应用程序调度提供了一种实用的解决方案。

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