CSR/AES: Enhancing Application Robustness via Adaptive and Cooperative Methods

随着高性能计算规模的持续增长，应用程序的健壮性变得越来越重要。检查点是传统的容错方法。但是，它只通过回滚处理发生故障后的故障。在一个进程发生故障的情况下，必须从故障前先前保存的状态重新启动包括非故障进程在内的所有进程。因此，由于工作丢失和故障恢复，可能导致显著的性能损失。主动式方法在故障发生前采取预防性措施(例如抢占式流程迁移)，从而以低成本避免故障。然而，它的有效性依赖于完美的故障预测，而这在实践中是很难实现的。该项目研究了一种称为自适应故障管理的新方法，它智能地集成了主动和被动的健壮性技术，使应用程序能够在可能的情况下避免预期的故障，并且在出现不可预见的故障的情况下，以将其影响保持在最小的方式容忍这些故障。该项目由三个主要部分组成：(1)协作式异常诊断(CAD)，通过开发元学习方法来改进大型系统中的故障预测；(2)自适应控制管理器(ACM)，用于响应不完美的故障预测而做出运行时决策；以及(3)集成运行时支持(IRS)，用于在运行时实现故障处理技术的经济高效协调。由此产生的框架将通过改善高性能计算应用程序在出现故障时的性能来增强其健壮性。该项目还加强了伊利诺伊理工学院的系统领域课程，并帮助培训未来一代的科学计算劳动力。

As the scale of high performance computing continues to grow, application robustness becomes increasingly important. Checkpointing is the conventional method for fault tolerance. However, it only deals with failures after their occurrence through rollback. In case of one process failure, all processes including non-faulty processes have to be restarted from the previously saved state prior to the failure. Thus, significant performance loss can be incurred due to the work loss and failure recovery. Proactive approaches take preventive actions (e.g. preemptive process migration) before failures, thereby avoiding failures with low cost. Nevertheless, its effectiveness relies on perfect fault prediction, which is hardly achievable in practice. This project investigates a new approach called adaptive fault management by intelligently integrating proactive and reactive robustness techniques such that it will enable applications to avoid anticipated faults if possible, and in the case of unforeseeable faults, to tolerate these faults in such a way that their impact is kept to a minimum. The project consists of three major components: (1) cooperative anomaly diagnosis (CAD) to improve fault prediction in large-scale systems by developing meta-learning methods; (2) adaptive control manager (ACM) to allow runtime decision making in response to imperfect fault prediction; and (3) integrated runtime support (IRS) to enable cost-effective coordination of fault handing techniques at runtime. The resulting framework will enhance robustness of high performance computing applications by improving their performance in the presence of failures. This project also enhances the systems-area curriculum at Illinois Institute of Technology and helps train the future-generation scientific computing workforce.