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On the run-time cost of distributed-memory communications generated using the polyhedral model

机译:关于使用多面体模型生成的分布式内存通信的运行时间成本

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The polyhedral model can be used to automatically generate distributed-memory communications for affine nested loops. Recently, new communication schemes that reduce the communication volume have been presented. In this paper we study the extra computational effort introduced at run-time by the code generated to manage the communication details across distributed processes. We focus on the most sophisticated communication scheme so far introduced (the FOP scheme). We present an asymptotic cost study of the FOP scheme in terms of two main run-time parameters: The problem size, and the number of processors. Based on this study, we identify scalability limitations in current implementations of these techniques, and propose a simple implementation alternative to eliminate one of them. Experimental results are presented, showing the potential impact on performance of these implementation limitations when using these codes in large parallel systems.
机译:多面体模型可用于自动生成用于仿射嵌套环的分布式存储器通信。最近,已经介绍了减少通信卷的新通信方案。在本文中,我们研究了生成的代码在运行时引入的额外计算工作来管理跨分布式进程的通信详细信息。我们专注于到目前为止介绍的最先进的通信计划(FOP方案)。我们在两个主要运行时参数方面提出了FOP方案的渐近成本研究:问题规模和处理器数量。基于这项研究,我们确定了这些技术的当前实现中的可扩展性限制,并提出了一种简单的实施方式来消除其中一个。提出了实验结果,显示了在大并行系统中使用这些代码时对这些实施限制的性能的潜在影响。

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