Ensemble Toolkit: Scalable and Flexible Execution of Ensembles of Tasks

Vivek Balasubramanian, Antons Treikalis, Ole Weidner, S. Jha
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引用次数: 35

Abstract

There are many science applications that require scalable task-level parallelism, support for flexible execution and coupling of ensembles of simulations. Most high-performance system software and middleware, however, are designed to support the execution and optimization of single tasks. Motivated by the missing capabilities of these computing systems and the increasing importance of task-level parallelism, we introduce the Ensemble toolkit which has the following application development features: (i) abstractions that enable the expression of ensembles as primary entities, and (ii) support for ensemble-based execution patterns that capture the majority of application scenarios. Ensemble toolkit uses a scalable pilot-based runtime system that decouples workload execution and resource management details from the expression of the application, and enables the efficient and dynamic execution of ensembles on heterogeneous computing resources. We investigate three execution patterns and characterize the scalability and overhead of Ensemble toolkit for these patterns. We investigate scaling properties for up to O(1000)concurrent ensembles and O(1000) cores and find linear weak and strong scaling behaviour.
集成工具箱:任务集成的可伸缩和灵活的执行
有许多科学应用需要可扩展的任务级并行性,支持灵活的执行和模拟集成的耦合。然而,大多数高性能系统软件和中间件都是为支持执行和优化单个任务而设计的。由于这些计算系统的功能缺失和任务级并行性日益重要,我们引入了集成工具包,它具有以下应用程序开发特性:(i)能够将集成表示为主要实体的抽象,以及(ii)支持捕获大多数应用程序场景的基于集成的执行模式。Ensemble工具包使用可伸缩的基于试点的运行时系统,该系统将工作负载执行和资源管理细节从应用程序的表达式中分离出来,并支持在异构计算资源上高效且动态地执行集成。我们研究了三种执行模式,并描述了这些模式的Ensemble工具包的可伸缩性和开销。我们研究了多达O(1000)个并发集成和O(1000)个内核的缩放特性,并发现了线性弱和强缩放行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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