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Exploiting duplication to minimize the execution times of parallel programs on message-passing systems

机译:利用重复以最小化消息传递系统上并行程序的执行时间

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Communication overhead is one of the main factors that can limit the speedup of parallel programs on message-passing parallel architectures. This limiting factor is more predominant in distributed systems such as clusters of homogeneous or heterogeneous workstations. However, excessive communication overhead can be reduced by redundantly executing some of the tasks of a parallel program on which other tasks critically depend. We study the problem of duplication-based static scheduling of parallel programs on parallel and distributed systems. Previous duplication-based scheduling algorithms assumed the availability of unlimited number of homogeneous processors. We consider more practical scenarios: when the number of processors is limited, and when the system consists of heterogeneous computers. For the first scenario, we propose an algorithm which minimizes the execution of a parallel program by controlling the level of duplication according to the number of processors available. For the second scenario, we design an algorithm which simultaneously exploits duplication and processor heterogeneity to minimize the total execution time of a parallel program. The proposed algorithms are suitable for low as well as high communication-to-computation ratios.
机译:通信开销是可以限制消息通过并行架构上并行程序的加速之一的主要因素之一。该限制因子在分布式系统中更主要是诸如均匀或异质工作站的簇的簇。然而,通过冗余执行其他任务尺寸依赖的并行程序的一些任务,可以减少过度的通信开销。我们研究了并行分布式系统上并行程序的复制基础静态调度问题。以前的基于复制的调度算法假设无限数量的同类处理器的可用性。我们考虑更实际的情况:当处理器的数量有限时,当系统由异构计算机组成时。对于第一场景,我​​们提出了一种算法,该算法通过根据可用的处理器的数量控制重复级别来最小化并行程序的执行。对于第二种情况,我们设计一种算法,它同时利用复制和处理器异质性,以最小化并行程序的总执行时间。所提出的算法适用于低以及高通信到计算比。

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