首页> 外文期刊>Parallel Computing >Characterizing MPI matching via trace-based simulation
【24h】

Characterizing MPI matching via trace-based simulation

机译:通过基于跟踪的仿真来表征MPI匹配

获取原文
获取原文并翻译 | 示例
           

摘要

With the increased scale expected on future leadership-class systems, detailed information about the resource usage and performance of MPI message matching provides important insights into how to maintain application performance on next-generation systems. However, obtaining MPI message matching performance data is often not possible without significant effort. A common approach is to instrument an MPI implementation to collect relevant statistics. While this approach can provide important data, collecting matching data at runtime perturbs the application’s execution, including its matching performance, and is highly dependent on the MPI library’s matchlist implementation. In this paper, we introduce a trace-based simulation approach to obtain detailed MPI message matching performance data for MPI applications without perturbing their execution. Using a number of key parallel workloads and microbenchmarks, we demonstrate that this simulator approach can rapidly and accurately characterize matching behavior. Specifically, we use our simulator to collect several important statistics about the operation of the MPI posted and unexpected queues. For example, we present data about search lengths and the duration that messages spend in the queues waiting to be matched. Data gathered using this simulation-based approach have significant potential to aid hardware designers in determining resource allocation for MPI matching functions and provide application and middleware developers with insight into the scalability issues associated with MPI message matching.
机译:随着未来领导层系统上规模的扩大,有关MPI消息匹配的资源使用和性能的详细信息将为如何维护下一代系统上的应用程序性能提供重要见解。但是,如果不花费大量精力,通常不可能获得与性能数据匹配的MPI消息。一种通用方法是对MPI实施进行检测以收集相关统计信息。尽管这种方法可以提供重要的数据,但在运行时收集匹配数据会扰乱应用程序的执行,包括其匹配性能,并且高度依赖MPI库的匹配列表实现。在本文中,我们介绍了一种基于跟踪的仿真方法,以获取MPI应用程序的详细MPI消息匹配性能数据,而不会影响它们的执行。使用许多关键的并行工作负载和微基准测试,我们证明了该模拟器方法可以快速而准确地表征匹配行为。具体来说,我们使用模拟器来收集有关MPI发布和意外队列操作的一些重要统计信息。例如,我们提供有关搜索长度和消息在等待匹配的队列中花费的持续时间的数据。使用这种基于仿真的方法收集的数据具有巨大的潜力,可帮助硬件设计人员确定MPI匹配功能的资源分配,并为应用程序和中间件开发人员提供与MPI消息匹配相关的可伸缩性问题的见解。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号