The Pheet Task-Scheduling Framework on the Intel® Xeon Phi Coprocessor and other Multicore Architectures

Martin Wimmer, Manuel Pöter, J. Träff
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引用次数: 9

Abstract

Pheet, a task-scheduling framework that allows for easy customization of internal data-structures, is a research vehicle for experimenting with high-level application and low-level architectural support for task-parallel programming models. Pheet is highly configurable, and allows comparison between different implementations of data structures used in the scheduler, as well as comparisons between entirely different schedulers (typically using work-stealing). Pheet is being used to investigate high-level task-parallel support mechanisms that allow applications to influence scheduling decisions and behavior. One such mechanism, that we use in this work, is scheduling strategies. Previous Pheet benchmarking was done on conventional multicore architectures from AMD and Intel. In this paper we discuss the performance of Pheet on a prototype Intel Xeon Phi coprocessor with 61 cores. We compare these results to Pheet on three conventional multicore architectures. Using two benchmarks from the mostly non-numerical/combinatorial Pheet suite we find that the Xeon Phi coprocessor provides considerably better scalability than the other architectures, with more than a 70x speedup on the 61-core Knights Corner prototype system when using 4-way SMT, although not achieving the same absolute performance. For our research, the Xeon Phi coprocessor is an interesting architecture for implementing and evaluating fine-grained task-parallel parallel algorithm implementations.
基于Intel®Xeon Phi协处理器和其他多核架构的工作表任务调度框架
Pheet是一个任务调度框架,允许轻松定制内部数据结构,它是一种研究工具,用于试验任务并行编程模型的高级应用程序和低级体系结构支持。sheet是高度可配置的,允许比较调度器中使用的不同数据结构实现,以及完全不同的调度器之间的比较(通常使用work-stealing)。sheet用于研究允许应用程序影响调度决策和行为的高级任务并行支持机制。我们在这项工作中使用的一种机制是调度策略。以前的sheet基准测试是在AMD和Intel的传统多核架构上完成的。本文讨论了Pheet在61核Intel Xeon Phi协处理器上的性能。我们将这些结果与三种传统多核架构上的pet进行比较。使用两个主要是非数字/组合pet套件的基准测试,我们发现Xeon Phi协处理器提供了比其他架构更好的可扩展性,当使用4路SMT时,在61核Knights Corner原型系统上加速超过70倍,尽管没有达到相同的绝对性能。对于我们的研究,Xeon Phi协处理器是实现和评估细粒度任务并行并行算法实现的有趣架构。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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