混合码的效率分析

Judit Giménez, Estanislao Mercadal, Germán Llort, Sandra Méndez
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引用次数: 0

摘要

混合并行化可能是大多数代码大规模使用高性能计算系统的唯一途径。即使在规模较小的情况下,随着每个节点的内核数量的增加,将MPI与一些基于线程的共享内存库相结合也可以减少应用程序的网络需求。尽管混合方法有好处,但要实现高效的混合执行并不容易。这不仅是因为组合两种不同的编程模型增加了复杂性,而且还因为在许多情况下,代码最初设计时只有一个并行化级别,后来扩展到混合模式。本文提出了诊断混合应用程序效率的模型,区分了每种并行编程范式的贡献。所提出的方法的灵活性允许我们将其用于不同的范例和场景,例如比较相同代码的MPI+OpenMP和MPI+CUDA版本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analyzing the Efficiency of Hybrid Codes
Hybrid parallelization may be the only path for most codes to use HPC systems on a very large scale. Even within a small scale, with an increasing number of cores per node, combining MPI with some shared memory thread-based library allows to reduce the application network requirements. Despite the benefits of a hybrid approach, it is not easy to achieve an efficient hybrid execution. This is not only because of the added complexity of combining two different programming models, but also because in many cases the code was initially designed with just one level of parallelization and later extended to a hybrid mode. This paper presents our model to diagnose the efficiency of hybrid applications, distinguishing the contribution of each parallel programming paradigm. The flexibility of the proposed methodology allows us to use it for different paradigms and scenarios, like comparing the MPI+OpenMP and MPI+CUDA versions of the same code.
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