SYMBIOSYS:一种可组合高性能计算数据服务的性能分析方法

Srinivasan Ramesh, A. Malony, P. Carns, R. Ross, Matthieu Dorier, Jérome Soumagne, S. Snyder
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引用次数: 0

摘要

由于其灵活性和可维护性,微服务是构建、定制和部署分布式服务的一种强大的新方式。已经出现了几个大型分布式平台,以满足商业计算中以数据为中心的工作负载和服务日益增长的需求。同时,高性能计算(HPC)系统和软件也在快速发展,以满足多样化和异构的应用需求。硬件因素、软件配置参数和微服务体系结构提供的灵活性的相互作用使得为给定的应用程序工作负载估计最佳服务实例化变得非常重要。此外,当考虑到这些服务在动态和异构的HPC环境中运行时,这个问题会更加严重。优化集成的服务可以比随意集成的服务性能高得多。现有的高性能计算性能工具要么无法理解微服务固有的通信请求-响应模型,要么在狭窄的范围内运行,从而限制了单独使用它们所能获得的洞察力。我们提出了一种名为SYMBIOSYS的高性能计算微服务框架和应用程序的集成性能分析方法。我们在Mochi框架的背景下描述它的设计和实现。这种集成是通过将分布式callpath分析和跟踪与性能数据交换策略相结合来实现的,该策略从RPC通信库和网络层收集细粒度的低级指标。其结果是一个可移植的、低开销的性能分析设置,它提供了微服务之间的依赖关系以及它们如何与Mochi RPC软件堆栈交互的整体配置文件。使用HEPnOS(生产质量的Mochi数据服务),我们演示了SYMBIOSYS的大规模低开销操作,并使用它来确定性能不佳的服务配置的根本原因。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SYMBIOSYS: A Methodology for Performance Analysis of Composable HPC Data Services
Microservices are a powerful new way of building, customizing, and deploying distributed services owing to their flexibility and maintainability. Several large-scale distributed platforms have emerged to serve the growing needs of data-centric workloads and services in commercial computing. Concurrently, high-performance computing (HPC) systems and software are rapidly evolving to meet the demands of diversified applications and heterogeneity. The interplay of hardware factors, software configuration parameters, and the flexibility offered with a microservice architecture makes it nontrivial to estimate the optimal service instantiation for a given application workload. Further, this problem is exacerbated when considering that these services operate in a dynamic and heterogeneous HPC environment. An optimally integrated service can be vastly more performant than a haphazardly integrated one. Existing performance tools for HPC either fail to understand the request-response model of communication inherent to microservices or they operate within a narrow scope, limiting the insight that can be gleaned from employing them in isolation.We propose a methodology for integrated performance analysis of HPC microservices frameworks and applications called SYMBIOSYS. We describe its design and implementation within the context of the Mochi framework. This integration is achieved by combining distributed callpath profiling and tracing with a performance data exchange strategy that collects fine-grained, low-level metrics from the RPC communication library and network layers. The result is a portable, low-overhead performance analysis setup that provides a holistic profile of the dependencies among microservices and how they interact with the Mochi RPC software stack. Using HEPnOS, a production-quality Mochi data service, we demonstrate the low-overhead operation of SYMBIOSYS at scale and use it to identify the root causes of poorly performing service configurations.
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