PPL:一个用于混合并行编程的抽象运行时系统

ESPM '15 Pub Date : 2015-11-15 DOI:10.1145/2832241.2832246
Alex Brooks, Hoang-Vu Dang, Nikoli Dryden, M. Snir
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引用次数: 5

摘要

硬件趋势表明,超级计算机的节点内并行性将快速增长。未来的编程模型将需要仔细管理节点间和节点内并行性之间的交互,以应对这种演变。有许多编程模型都暴露了这两种并行度。然而,随着每个节点线程数量的增加,它们不能很好地扩展,并且线程和通信之间的互操作性有限,从而导致不必要的软件开销和不必要的通信数量的增加。为了解决这个问题,有必要了解当前模型的局限性并开发新的方法。我们提出了一种新的运行时系统设计,PPL,它抽象了一个典型的分布式存储机器并行系统的重要高层概念。通过模块化这些元素,可以对层进行测试,以便更好地理解未来编程模型的需求。我们详细介绍了在c++ 11中PPL的设计和开发实现,并通过微基准测试和三个应用程序(Barnes-Hut、Monte Carlo粒子跟踪和稀疏三角形求解器)评估了几个不同模块实现的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PPL: an abstract runtime system for hybrid parallel programming
Hardware trends indicate that supercomputers will see fast growing intra-node parallelism. Future programming models will need to carefully manage the interaction between inter- and intra-node parallelism to cope with this evolution. There exist many programming models which expose both levels of parallelism. However, they do not scale well as per-node thread counts rise and there is limited interoperability between threading and communication, leading to unnecessary software overheads and an increased amount of unnecessary communication. To address this, it is necessary to understand the limitations of current models and develop new approaches. We propose a new runtime system design, PPL, which abstracts important high-level concepts of a typical parallel system for distributed-memory machines. By modularizing these elements, layers can be tested to better understand the needs of future programming models. We present details of the design and development implementation of PPL in C++11 and evaluate the performance of several different module implementations through micro-benchmarks and three applications: Barnes-Hut, Monte Carlo particle tracking, and a sparse-triangular solver.
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