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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >Messages Scheduling for Parallel Data Redistribution between Clusters
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Messages Scheduling for Parallel Data Redistribution between Clusters

机译：集群之间并行数据重新分配的消息调度

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摘要

We study the problem of redistributing data between clusters interconnected by a backbone. We suppose that at most k communications can be performed at the same time (the value of k depending on the characteristics of the platform). Given a set of messages, we aim at minimizing the total communication time assuming that communications can be preempted and that preemption comes with an extra cost. Our problem, called k{hbox{-}}Preemptive Bipartite Scheduling (KPBS) is proven to be NP-hard. We study its lower bound. We propose two {frac{8}{3}}{hbox{-}}{rm{approximation}} algorithms with low complexity and fast heuristics. Simulation results show that both algorithms perform very well compared to the optimal solution and to the heuristics. Experimental results, based on an MPI implementation of these algorithms, show that both algorithms outperform a brute-force TCP-based solution, where no scheduling of the messages is performed.
机译：我们研究了在由主干互连的集群之间重新分配数据的问题。我们假设最多可以同时执行k个通信（k的值取决于平台的特性）。在给定一组消息的情况下，我们旨在最大程度地缩短总通信时间，前提是可以抢占通信，而抢占会产生额外费用。我们的问题称为k {hbox {-}}，抢占式双向调度（KPBS）已证明是NP难的。我们研究其下限。我们提出了两种{frac {8} {3}} {hbox {-}} {rm {approximation}}算法，它们具有低复杂度和快速启发式算法。仿真结果表明，与最优解和启发式算法相比，两种算法的性能都很好。基于这些算法的MPI实现的实验结果表明，这两种算法都优于基​​于蛮力TCP的解决方案，该解决方案不执行消息调度。

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