用复制映射流水线应用程序以提高吞吐量和可靠性

A. Benoit, L. Marchal, Y. Robert, O. Sinnen
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引用次数: 5

摘要

将应用程序映射和调度到并行系统的处理器上是一个难题。当性能是唯一的目标时,情况确实如此,但当涉及到第二个优化标准(如可靠性)时,情况就变得更糟了。在本文中,我们研究了将由几个连续阶段组成的应用程序(即管道)映射到异构处理器上的问题,同时考虑了性能(以吞吐量衡量)和可靠性。复制机制指的是将一个应用程序阶段映射到多个处理器上,可以用来提高吞吐量,也可以提高可靠性。找到正确的复制权衡对于这个双条件优化问题起着关键作用。我们的正式模型包括异构处理器,在执行速度和可靠性方面都是如此。我们研究了各种子问题的复杂性,并展示了如何获得多项式情况的解。对于一般NP-hard问题,提出了启发式方法并进行了实验评估。我们进一步提出了一种基于A*状态空间搜索的精确算法的设计,它允许我们评估我们的启发式算法在小问题实例中的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mapping Pipelined Applications with Replication to Increase Throughput and Reliability
Mapping and scheduling an application onto the processors of a parallel system is a difficult problem. This is true when performance is the only objective, but becomes worse when a second optimization criterion like reliability is involved. In this paper we investigate the problem of mapping an application consisting of several consecutive stages, i.e., a pipeline, onto heterogeneous processors, while considering both the performance, measured as throughput, and the reliability. The mechanism of replication, which refers to the mapping of an application stage onto more than one processor, can be used to increase throughput but also to increase reliability. Finding the right replication trade-off plays a pivotal role for this bi-criteria optimization problem. Our formal model includes heterogeneous processors, both in terms of execution speed as well as in terms of reliability. We study the complexity of the various sub problems and show how a solution can be obtained for the polynomial cases. For the general NP-hard problem, heuristics are presented and experimentally evaluated. We further propose the design of an exact algorithm based on A* state space search which allows us to evaluate the performance of our heuristics for small problem instances.
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