Collaborative Research: CSR-SMA+AES: Pro-Active Runtime Health Enhancement of Large-Scale Parallel Systems Using PROGNOSIS

大规模并行系统对于应对高要求应用所带来的挑战至关重要。推动硬件和软件技术的极限以获取最大性能可能会增加它们对故障的敏感性。这是硬件瞬态错误、硬件设备故障和软件复杂性不断增加的结果。这些故障可能会对系统性能产生重大影响，并增加维护/操作成本，从而使部署这些大规模系统的动机处于危险之中。该项目不是将故障视为异常并采取主动补救措施，而是打算预测它们的发生，并采取主动的运行时措施来隐藏它们的影响。这项研究有望在开发运行时容错基础设施方面做出三个广泛的贡献。第一组贡献是在一段较长时间内从实际的BlueGene/L系统收集和分析系统事件。第二组贡献是在线分析和预测不断变化的故障数据的模型。第三组贡献是关于故障感知并行作业调度和检查点。在教育方面，除了加强研究生课程和研究外，该项目还打算让本科生和妇女参与进来。本项目开发的工具和相关结果将在公共领域提供，并在主要期刊/会议上发表。此外，pi还将推动将这些工具集成到实际系统中，以增强它们的容错能力。

Large scale parallel systems are critical to take on the challenges imposed by highly demanding applications of critical importance. Pushing the limits of hardware and software technologies to extract the maximum performance can increase their susceptibility to failures. This arises as a consequence of growing hardware transient errors, hardware device failures, and software complexity. These failures can have substantial consequences on system performance, and add to the costs of maintenance/operation, thereby putting at risk the very motivation behind deploying these large scale systems. Rather than treat failures as an exception and takereactive remedies, this project intends to anticipate their occurrence and take pro-active runtime measures to hide their impact.This research is expected to make three broad contributions towardsdeveloping a runtime fault-tolerance infrastructure.The first set of contributions is on collecting and analyzingsystem events from an actual BlueGene/L system over anextended period of time. The second set of contributions are models foronline analysis and prediction of evolving failure data.The third set of contributions are on failure-aware parallel job scheduling and checkpointing. On the educational front, in addition to enhancing graduate curriculum and research, this project intends to involve undergraduate students and women. The tools developed in this project and the related results will be made available in public domain and published in leading journals/conferences. In addition, the PIs will also push these tools to be incorporated on actual systems, to enhance their fault-toleranceabilities.