Chapel-on-X: Exploring Tasking Runtimes for PGAS Languages

Akihiro Hayashi, S. Paul, M. Grossman, J. Shirako, Vivek Sarkar
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引用次数: 12

Abstract

With the shift to exascale computer systems, the importance of productive programming models for distributed systems is increasing. Partitioned Global Address Space (PGAS) programming models aim to reduce the complexity of writing distributed-memory parallel programs by introducing global operations on distributed arrays, distributed task parallelism, directed synchronization, and mutual exclusion. However, a key challenge in the application of PGAS programming models is the improvement of compilers and runtime systems. In particular, one open question is how runtime systems meet the requirement of exascale systems, where a large number of asynchronous tasks are executed. While there are various tasking runtimes such as Qthreads, OCR, and HClib, there is no existing comparative study on PGAS tasking/threading runtime systems. To explore runtime systems for PGAS programming languages, we have implemented OCR-based and HClib-based Chapel runtimes and evaluated them with an initial focus on tasking and synchronization implementations. The results show that our OCR and HClib-based implementations can improve the performance of PGAS programs compared to the existing Qthreads backend of Chapel.
Chapel-on-X:探索PGAS语言的任务处理运行时
随着向百亿亿级计算机系统的转变,分布式系统的生产性编程模型的重要性正在增加。分区全局地址空间(PGAS)编程模型旨在通过在分布式数组上引入全局操作、分布式任务并行性、定向同步和互斥来降低编写分布式内存并行程序的复杂性。然而,PGAS编程模型应用中的一个关键挑战是编译器和运行时系统的改进。特别是,一个悬而未决的问题是运行时系统如何满足执行大量异步任务的百亿亿级系统的需求。虽然有各种各样的任务运行时,如Qthreads、OCR和HClib,但目前还没有对PGAS任务/线程运行时系统进行比较研究。为了探索PGAS编程语言的运行时系统,我们实现了基于ocr和基于hclib的Chapel运行时,并对它们进行了评估,最初的重点是任务和同步实现。结果表明,与Chapel现有的Qthreads后端相比,基于OCR和hclib的实现可以提高PGAS程序的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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