Online Scheduling of Moldable Task Graphs under Common Speedup Models

A. Benoit, Lucas Perotin, Y. Robert, Hongyang Sun
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引用次数: 2

Abstract

The problem of scheduling moldable tasks on multiprocessor systems with the objective of minimizing the overall completion time (or makespan) has been widely studied, in particular when tasks have dependencies (i.e., task graphs), or when tasks are released on-the-fly (i.e., online). However, few studies have focused on both (i.e., online scheduling of moldable task graphs). In this paper, we design a new online algorithm and derive constant competitive ratios for this problem under several common yet realistic speedup models (i.e., roofline, communication, Amdahl, and a general combination). We also prove, for each model, a lower bound on the competitiveness of our algorithm, which is very close to the constant competitive ratio. Finally, we provide the first lower bound on the competitive ratio of any deterministic online algorithm for the arbitrary speedup model, which is not constant but depends on the number of tasks in the longest path of the graph.
常用加速模型下可塑任务图的在线调度
以最小化总体完成时间(或makespan)为目标,在多处理器系统上调度可建模任务的问题已经得到了广泛的研究,特别是当任务具有依赖性(即任务图)或当任务实时释放(即在线)时。然而,很少有研究同时关注两者(即可建模任务图的在线调度)。在本文中,我们设计了一种新的在线算法,并在几种常见但现实的加速模型(即rooline, communication, Amdahl和一般组合)下推导出该问题的恒定竞争比。我们还证明了对于每个模型,我们的算法的竞争力的下界,它非常接近于常数竞争比。最后,我们给出了任意加速模型下任何确定性在线算法的竞争比的第一个下界,它不是恒定的,而是取决于图中最长路径上的任务数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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