TaPS：面向基于任务的执行框架的性能评估套件
TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks
AI总结：
针对基于任务的执行框架缺乏统一评估标准难以对比的问题，提出TaPS任务性能套件，提供统一模块化接口与参考应用集，可支撑框架的可靠评估。
摘要：
基于任务的执行框架（例如并行编程库、计算工作流系统和函数即服务平台）支持将不同任务组合为单个统一应用，以达成计算目标。这类框架可对应用任务在任意硬件上的并行执行进行抽象。随着计算科学愈发需要利用并行计算和/或异构硬件，针对这类任务执行器的研究增速加快。然而，评估标准的缺失使得新系统与现有实现之间的对比与参照颇具难度。本文提出TaPS（任务性能套件），为并行任务执行器框架的持续研究提供支撑。TaPS具备两大特性：（1）统一的模块化接口，可借助任意执行框架与数据管理系统编写和评估应用；（2）首批参考合成应用与真实科学应用集合。本文探讨了TaPS的设计如何支撑框架的可靠评估，并通过使用所提供参考应用的基准测试调研，展示了TaPS的效用。
英文摘要：
Task-based execution frameworks, such as parallel programming libraries, computational workflow systems, and function-as-a-service platforms, enable the composition of distinct tasks into a single, unified application designed to achieve a computational goal. Task-based execution frameworks abstract the parallel execution of an application's tasks on arbitrary hardware. Research into these task executors has accelerated as computational sciences increasingly need to take advantage of parallel compute and/or heterogeneous hardware. However, the lack of evaluation standards makes it challenging to compare and contrast novel systems against existing implementations. Here, we introduce TaPS, the Task Performance Suite, to support continued research in parallel task executor frameworks. TaPS provides (1) a unified, modular interface for writing and evaluating applications using arbitrary execution frameworks and data management systems and (2) an initial set of reference synthetic and real-world science applications. We discuss how the design of TaPS supports the reliable evaluation of frameworks and demonstrate TaPS through a survey of benchmarks using the provided reference applications.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
