全程序间集体验证的PARCOACH扩展

Pierre Huchant, Emmanuelle Saillard, Denis Barthou, Hugo Brunie, Patrick Carribault
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引用次数: 5

摘要

百亿亿级的出现需要更具可扩展性和更高效的技术来帮助开发人员定位、分析和纠正并行应用程序中的错误。并行控制流异常检查器(PARCOACH)是一个框架,用于检测使用MPI和/或OpenMP的应用程序中集体错误的起源。在MPI中,这些错误包括集体操作不匹配。在OpenMP中,集体错误可能是团队中所有任务都无法调用的障碍。在本文中,我们提出了PARCOACH的扩展,改进了它的集体错误检测。在不同的基准测试和实际应用程序中,我们的分析比之前的分析更精确和准确。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PARCOACH Extension for a Full-Interprocedural Collectives Verification
The advent to exascale requires more scalable and efficient techniques to help developers to locate, analyze and correct errors in parallel applications. PARallel COntrol flow Anomaly CHecker (PARCOACH) is a framework that detects the origin of collective errors in applications using MPI and/or OpenMP. In MPI, such errors include collective operations mismatches. In OpenMP, a collective error can be a barrier not called by all tasks in a team. In this paper, we present an extension of PARCOACH which improves its collective errors detection. We show our analysis is more precise and accurate than the previous one on different benchmarks and real applications.
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