An adaptive mesh refinement benchmark for modern parallel programming languages

Tong Wen, Jimmy Su, P. Colella, K. Yelick, N. Keen
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引用次数: 19

Abstract

We present an Adaptive Mesh Refinement benchmark for evaluating programmability and performance of modern parallel programming languages. Benchmarks employed today by language developing teams, originally designed for performance evaluation of computer architectures, do not fully capture the complexity of state-of-the-art computational software systems running on today's parallel machines or to be run on the emerging ones from the multi-cores to the peta-scale High Productivity Computer Systems. This benchmark, extracted from a real application framework, presents challenges for a programming language in both expressiveness and performance. It consists of an infrastructure for finite difference calculations on block-structured adaptive meshes and a solver for elliptic Partial Differential Equations built on this infrastructure. Adaptive Mesh Refinement algorithms are challenging to implement due to the irregularity introduced by local mesh refinement. We describe those challenges posed by this benchmark through two reference implementations (C++ /Fortran/MPI and Titanium) and in the context of three programming models.
现代并行编程语言的自适应网格细化基准
我们提出了一个自适应网格细化基准来评估现代并行编程语言的可编程性和性能。语言开发团队今天使用的基准测试,最初是为计算机体系结构的性能评估而设计的,并不能完全捕捉到在当今并行机器上运行的最先进的计算软件系统的复杂性,也不能完全捕捉到在从多核到千万亿级高生产率计算机系统的新兴计算机上运行的复杂性。这个基准测试是从实际应用程序框架中提取出来的,它在表达性和性能方面都对编程语言提出了挑战。它包括用于块结构自适应网格的有限差分计算的基础结构和基于该基础结构的椭圆偏微分方程求解器。由于局部网格细化带来的不规则性,自适应网格细化算法难以实现。我们通过两个参考实现(c++ /Fortran/MPI和Titanium)和三种编程模型的上下文中描述了这个基准所带来的挑战。
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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