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Tail queues: A multi-threaded matching architecture

机译:尾部队列:多线程匹配架构

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As we approach exascale, computational parallelism will have to drastically increase in order to meet throughput targets. Many-core architectures have exacerbated this problem by trading reduced clock speeds, core complexity, and computation throughput for increasing parallelism. This presents two major challenges for communication libraries such as MPI: the library must leverage the performance advantages of thread level parallelism and avoid the scalability problems associated with increasing the number of processes to that scale. Hybrid programming models, such as MPI+X, have been proposed to address these challenges. MPI THREAD MULTIPLE is MPI's thread safe mode. While there has been work to optimize it, it largely remains non-performant in most implementations. While current applications avoid MPI multithreading due to performance concerns, it is expected to be utilized in future applications. One of the major synchronous data structures required by MPI is the matching engine. In this paper, we present a parallel matching algorithm that can improve MPI matching for multithreaded applications. We then perform a feasibility study to demonstrate the performance benefit of the technique.
机译:随着我们接近万亿级,为了满足吞吐量目标,计算并行性将必须急剧增加。许多内核体系结构通过降低时钟速度,内核复杂性和计算吞吐量以提高并行度来加剧该问题。这给诸如MPI之类的通信库提出了两个主要挑战:库必须利用线程级并行性的性能优势,并避免与将进程数量增加到该规模有关的可伸缩性问题。已经提出了混合编程模型(例如MPI + X)来解决这些挑战。 MPI THREAD MULTIPLE是MPI的线程安全模式。尽管已经进行了一些优化工作,但是在大多数实现中,它仍然表现不佳。尽管当前的应用程序出于性能考虑而避免了MPI多线程,但预期将在以后的应用程序中使用它。 MPI所需的主要同步数据结构之一是匹配引擎。在本文中,我们提出了一种并行匹配算法,该算法可以改善多线程应用程序的MPI匹配。然后,我们进行可行性研究,以证明该技术的性能优势。

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