Novel List Scheduling Strategies for Data Parallelism Task Graphs

Yang Liu, Lin Meng, Ittetsu Taniguchi, H. Tomiyama
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引用次数: 15

Abstract

This paper studies task scheduling algorithms which schedule a set of tasks on multiple cores so that the total scheduling length is minimized. Most of the algorithms developed in the past assume that a task is executed on a single core. Unlike the previous algorithms, the algorithms studied in this paper allow a task to be executed on multiple cores. This paper proposes six algorithms. All of the six algorithms are based on list scheduling, but the strategy for priority assignment is different. In our experiments, the six algorithms as well as an integer linear programming method are evaluated.Â
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数据并行任务图的新型列表调度策略
本文研究了任务调度算法,该算法将一组任务调度到多个核上,使调度总长度最小。过去开发的大多数算法都假设任务是在单核上执行的。与以往的算法不同,本文研究的算法允许在多个核心上执行任务。本文提出了六种算法。这六种算法都基于列表调度,但优先级分配策略不同。在我们的实验中,这六种算法以及一种整数线性规划方法是evaluated.Â
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