SI2-SSI: Collaborative Proposal: Performance Application Programming Interface for Extreme-Scale Environments (PAPI-EX)

现代高性能计算（HPC）系统在尺寸和复杂性上持续增加。在这些日益复杂的环境中测量应用程序性能的工具还必须增加其测量的丰富性，以深入了解软件和硬件交互的日益复杂的方式。PAPI性能监控库为所有现代CPU和其他感兴趣的组件（分散在芯片和系统中）上可用的硬件性能计数器提供了一个清晰、便携的接口。广泛部署和广泛使用，PAPI已经成为基础软件基础设施，不仅适用于科学计算社区，也适用于许多HPC行业用户。 但是，过去几年来，处理器和系统设计发生了根本性的变化，这对PAPI和整个HPC软件基础设施提出了新的挑战。 PAPI-EX项目整合了来自政府和行业研究投资的关键PAPI增强功能，重点关注处理器和系统设计变化，这些变化预计将出现在通往百亿亿次计算的道路上的每一个极端规模平台上。PAPI-EX的主要影响是PAPI库的重要性的直接函数。PAPI已经被工具开发人员、主要的国家HPC中心、系统供应商和应用程序开发人员使用了超过15年。PAPI-EX建立在这个基础上。作为重要的研究基础设施，PAPI-EX项目使PAPI能够在新系统的设计和规模发生革命性变化时继续发挥其重要作用。在加强发现和教育方面，与PAPI-EX合作的合作伙伴名单包括NSF计算中心，主要工具开发商，主要系统供应商和个别社区领导人，这个多元化的团体将有助于促进培训课程，有针对性的研讨会和小型研讨会在国家和国际会议上。最后，许多主要系统供应商对PAPI的积极推广意味着PAPI以及PAPI-EX将继续在许多领域为政府和行业带来重大利益。PAPI-EX解决了当前和未来多核CPU的核心共享各种性能关键资源（即，“核间”资源），包括功率管理、片上网络、存储器层次结构和核之间的存储器控制器。未能管理这些"内核间"资源的争用已经成为影响整体应用程序性能的主要因素。因此，对于许多性能工具（例如，TAU，HPCToolkit，开放|SpeedShop、Vampir、Scalasca、CrayPat、Active Harmony等）。PAPI-EX增强和扩展了PAPI，以解决这一关键问题，并使其在HPC性能优化中发挥其公认的作用。因此，PAPI-EX的目标如下：（1）开发共享的硬件计数器支持，包括系统范围内和内核间的测量;（2）提供支持的数据流为基础的运行时系统;（3）创建一个采样接口，以记录流的性能数据与相关的上下文;（4）联合收割机一个易于使用的工具，基于文本的应用程序性能分析与更新PAPI？的高级API来创建一个基本的，？从盒子里出来？插装API。

Modern High Performance Computing (HPC) systems continue to increase in size and complexity. Tools to measure application performance in these increasingly complex environments must also increase the richness of their measurements to provide insights into the increasingly intricate ways in which software and hardware interact. The PAPI performance-monitoring library has provided a clear, portable interface to the hardware performance counters available on all modern CPUs and some other components of interest (scattered across the chip and system). Widely deployed and widely used, PAPI has established itself as fundamental software infrastructure, not only for the scientific computing community, but for many industry users of HPC as well. But the radical changes in processor and system design that have occurred over the past several years pose new challenges to PAPI and the HPC software infrastructure as a whole. The PAPI-EX project integrates critical PAPI enhancements that flow from both governmental and industry research investments, focusing on processor and system design changes that are expected to be present in every extreme scale platform on the path to exascale computing.The primary impact of PAPI-EX is a direct function of the importance of the PAPI library. PAPI has been in predominant use by tool developers, major national HPC centers, system vendors, and application developers for over 15 years. PAPI-EX builds on that foundation. As important research infrastructure, the PAPI-EX project allows PAPI to continue to play its essential role in the face of the revolutionary changes in the design and scale of new systems. In terms of enhancing discovery and education, the list of partners working with PAPI-EX includes NSF computing centers, major tool developers, major system vendors, and individual community leaders, and this diverse group will help facilitate training sessions, targeted workshops, and mini-symposia at national and international meetings. Finally, the active promotion of PAPI by many major system vendors means that PAPI, and therefore PAPI-EX, will continue to deliver major benefits for government and industry in many domains.PAPI-EX addresses a hardware environment in which the cores of current and future multicore CPUs share various performance-critical resources (a.k.a., 'inter-core' resources), including power management, on-chip networks, the memory hierarchy, and memory controllers between cores. Failure to manage contention for these 'inter-core' resources has already become a major drag on overall application performance. Consequently, the lack of ability to reveal the actual behavior of these resources at a low level, has become very problematic for the users of the many performance tools (e.g., TAU, HPCToolkit, Open|SpeedShop, Vampir, Scalasca, CrayPat, Active Harmony, etc.). PAPI-EX enhances and extends PAPI to solve this critical problem and prepare it to play its well-established role in HPC performance optimization. Accordingly, PAPI-EX targets the following objectives: (1) Develop shared hardware counter support that includes system-wide and inter-core measurements; (2) Provide support for data-flow based runtime systems; (3) Create a sampling interface to record streams of performance data with relevant context; (4) Combine an easy-to-use tool for text-based application performance analysis with updates to PAPI?s high-level API to create a basic, ?out of the box? instrumentation API.