基于MPI派生数据类型的预期和观察通信性能

Alexandra Carpen-Amarie, S. Hunold, J. Träff
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引用次数: 10

摘要

我们使用MPI派生的数据类型来检查对通信性能的自然期望,并将其与基线、通信简单、不连续数据布局的“原始”性能进行比较。我们展示了常见的MPI库有时会违反这些数据类型性能预期,并讨论了发生这种情况的原因,还展示了MPI库表现良好的情况。我们的发现在很多方面都令人惊讶和失望。首先,派生数据类型的性能有时比使用相应的MPI功能进行语义等价的打包和解包更差。其次,MPI标准中规定的单个连续数据类型与其组成数据类型的重复之间的通信性能等价并不是普遍适用的。第三,MPI库在类型提交时通常使用的启发式方法不足以强制执行自然的性能准则,而更好的类型规范化启发式方法可能会对性能产生重大影响。我们展示了所有MPI类型构造函数都是实现某些数据布局预期性能所必需的情况。我们描述了验证数据类型性能准则的基准测试方法,并提供了针对不同MPI库的广泛验证结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Expected and Observed Communication Performance with MPI Derived Datatypes
We examine natural expectations on communication performance using MPI derived datatypes in comparison to the baseline, "raw" performance of communicating simple, noncontiguous data layouts. We show that common MPI libraries sometimes violate these datatype performance expectations, and discuss reasons why this happens, but also show cases where MPI libraries perform well. Our findings are in many ways surprising and disappointing. First, the performance of derived datatypes is sometimes worse than the semantically equivalent packing and unpacking using the corresponding MPI functionality. Second, the communication performance equivalence stated in the MPI standard between a single contiguous datatype and the repetition of its constituent datatype does not hold universally. Third, the heuristics that are typically employed by MPI libraries at type-commit time are insufficient to enforce natural performance guidelines, and better type normalization heuristics may have a significant performance impact. We show cases where all the MPI type constructors are necessary to achieve the expected performance for certain data layouts. We describe our benchmarking approach to verify the datatype performance guidelines, and present extensive verification results for different MPI libraries.
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