PaRSEC在实践中:通过分布式任务执行优化遗留化学应用

Anthony Danalis, Heike Jagode, G. Bosilca, J. Dongarra
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引用次数: 22

摘要

基于任务的执行作为一种在后千万亿级时代提供性能和可移植性之间良好平衡的手段,已经越来越受欢迎。并行运行时调度和执行控制(PARSEC)框架是一个基于任务的运行时系统,我们设计它是为了实现大规模的高性能计算。PARSEC提供了一种编程范式,与传统上用于开发大规模并行科学应用程序的编程范式不同。在本文中,我们讨论了使用PARSEC将量子化学包NWCHEM的耦合簇(CC)组件的一部分转换为基于任务的形式。我们解释了如何在单个任务中组织CC方法的计算,并明确定义了它们之间的数据依赖关系,并将修改后的代码重新集成到NWCHEM中。我们提出了一个彻底的性能评估,并证明修改后的代码比原来的代码性能好两倍以上。我们还比较了修改后代码的不同变体的性能,并解释了导致性能差异的不同行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PaRSEC in Practice: Optimizing a Legacy Chemistry Application through Distributed Task-Based Execution
Task-based execution has been growing in popularity as a means to deliver a good balance between performance and portability in the post-petascale era. The Parallel Runtime Scheduling and Execution Control (PARSEC) framework is a task-based runtime system that we designed to achieve high performance computing at scale. PARSEC offers a programming paradigm that is different than what has been traditionally used to develop large scale parallel scientific applications. In this paper, we discuss the use of PARSEC to convert a part of the Coupled Cluster (CC) component of the Quantum Chemistry package NWCHEM into a task-based form. We explain how we organized the computation of the CC methods in individual tasks with explicitly defined data dependencies between them and re-integrated the modified code into NWCHEM. We present a thorough performance evaluation and demonstrate that the modified code outperforms the original by more than a factor of two. We also compare the performance of different variants of the modified code and explain the different behaviors that lead to the differences in performance.
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