CSR: Rethinking System Software for Overprovisioned, High-Performance Computing Systems

目前，高性能计算(HPC)社区专注于实现exaflop性能，这大约是当今世界上最好的超级计算机性能的30倍。出于实际、财务和环境方面的考虑，能源部将实现exaflop的功率限制在20兆瓦。由于今天的顶级机器通常消耗5到20兆瓦-但距离exaflop性能目标有一个数量级或更大的距离，高性能计算系统中的重大硬件和软件改进是必要的。改进硬件的一种方法是使用过度配置的系统，这些系统包含的机器比同时完全供电的机器还多。虽然过度配置的系统有可能显著提高功率和性能，但软件将需要重新设计以支持此类系统。本提案的重点是设计和实施支持过度配置的系统的软件基础设施。基础设施的关键进步是支持系统范围的优化，即跨多个应用程序的优化。这与当前HPC系统中以每个应用程序为基础进行优化的重点形成了鲜明对比。开发的软件将包括作业剖析器、一次对多个作业执行分析的调度器以及基于调度器分析的输出联合优化多个应用程序的集群范围运行时系统。实现亿级计算是国家的重要优先事项，将影响许多关键应用领域，如气候/天气、可再生能源、核能、材料科学和国家安全。本文所描述的工作将提高功率受限高性能计算系统的整体性能，这是朝着艾级目标迈出的重要一步。该项目计划通过与几个国家实验室的长期合作，以拟议的软件堆栈的形式转让这项研究产生的技术。

Currently, the high-performance computing (HPC) community is focused on achieving exaflop performance, which is about a 30-fold improvement from the performance of the best supercomputer in the world today. Because of practical, financial, and environmental concerns, the Department of Energy is setting a power limit for achieving an exaflop at 20 megawatts. As today's top machines generally consume between five and 20 megawatts---and yet are an order of magnitude or more away from the exaflop performance target, significant hardware and software advances in HPC systems are necessary. One way to improve hardware is to use overprovisioned systems, which contain more machines than can be fully powered simultaneously. While overprovisioned systems have the potential to significantly improve power and performance, software will need to be redesigned to support such systems.The focus of this proposal is to design and implement software infrastructure that will support overprovisioned systems. The key advance in the infrastructure is support of system-wide optimizations, i.e., optimizations that span multiple applications. This is in stark contrast to the current focus in HPC systems of optimizing on a per-application basis. The developed software will consist of a job profiler, a scheduler that performs analysis on multiple jobs at a time, and a cluster-wide run-time system that jointly optimizes multiple applications based on the output of the scheduler analysis.Achieving exascale computing is an important national priority and will impact many critical application domains, such as climate/weather, renewable energy, nuclear energy, materials science, and national security. The work described here will improve whole-system performance on power-constrained HPC systems, which is one important step towards the exascale goal. The project plans to transfer technology resulting from this research in the form of the proposed software stack via longstanding collaborations with several national laboratories.