Summit上多任务执行性能的表征
Characterizing the Performance of Executing Many-tasks on Summit
摘要：
许多科学工作负载由许多任务组成，其中每个任务都是独立的模拟或数据分析。在异构HPC平台上执行数百万任务需要可扩展的动态资源管理和多级调度。RADICAL-Pilot（RP）-Pilot抽象的实现，解决了这些挑战，并作为一个有效的运行时系统来执行由许多任务组成的工作负载。在本文中，我们使用RP执行多个任务时，与JSM和PRRTE接口的性能：RP是负责资源管理和任务调度上获得的资源; JSM或PRRTE制定的位置启动调度任务。我们的实验提供了较低的边界上的RP的性能时，与JSM和PRRTE集成。具体来说，对于由同构单核组成的工作负载，15分钟长的任务，我们发现：对于> O（1000）任务，PRRTE的扩展性优于JSM; PRRTE开销可以忽略不计; PRRTE支持优化，降低开销的影响，并在404个计算节点上执行O（16 K）单核任务时实现63%的资源利用率。
英文摘要：
Many scientific workloads are comprised of many tasks, where each task is an independent simulation or analysis of data. The execution of millions of tasks on heterogeneous HPC platforms requires scalable dynamic resource management and multi-level scheduling. RADICAL-Pilot (RP) -- an implementation of the Pilot abstraction, addresses these challenges and serves as an effective runtime system to execute workloads comprised of many tasks. In this paper, we characterize the performance of executing many tasks using RP when interfaced with JSM and PRRTE on Summit: RP is responsible for resource management and task scheduling on acquired resource; JSM or PRRTE enact the placement of launching of scheduled tasks. Our experiments provide lower bounds on the performance of RP when integrated with JSM and PRRTE. Specifically, for workloads comprised of homogeneous single-core, 15 minutes-long tasks we find that: PRRTE scales better than JSM for > O(1000) tasks; PRRTE overheads are negligible; and PRRTE supports optimizations that lower the impact of overheads and enable resource utilization of 63% when executing O(16K), 1-core tasks over 404 compute nodes.
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。
