从瞬时错误引起的崩溃中恢复近零停机时间
Near-zero Downtime Recovery from Transient-error-induced Crashes
摘要：
由于系统缩放，由外部噪声引起的瞬态误差，例如，热通量和粒子撞击已经成为当前和即将到来的极端规模高性能计算（HPC）系统的日益关注的问题。然而，由于与无故障情况相比，这样的错误仍然非常罕见，因此期望的解决方案要求低/无开销系统，其在无故障条件下不损害性能并且还允许非常快速的故障恢复以最小化停机时间。在本文中，我们提出了IterPro，一个轻量级的编译器辅助的弹性技术，快速，准确地从瞬态错误引起的崩溃恢复进程。IterPro在发生错误时即时修复损坏的进程状态，使应用程序能够继续执行而不是终止。IterPro还利用基于归纳变量的代码优化技术引入的副作用来提高其恢复能力。为此，引入了两个新的代码转换通道，以暴露用于恢复目的的副作用。我们使用4个科学工作负载以及NPB基准测试套件评估了IterPro。在正常执行期间，IterPro几乎没有运行时开销，只有一个小的固定的27 MB内存开销。与此同时，IterPro可以在几十毫秒内恢复平均83.55%的导致崩溃的错误，停机时间可以忽略不计。有了这样一个有效的恢复机制，IterPro可以极大地减轻未来极端规模系统中弹性子系统的开销和资源需求。
英文摘要：
Due to the system scaling, transient errors caused by external noises, e.g., heat fluxes and particle strikes, have become a growing concern for the current and upcoming extreme-scale high-performance-computing (HPC) systems. However, since such errors are still quite rare as compared to no-fault cases, desirable solutions call for low/no-overhead systems that do not compromise the performance under no-fault conditions and also allow very fast fault recovery to minimize downtime. In this paper, we present IterPro, a light-weight compiler-assisted resilience technique to quickly and accurately recover processes from transient-error-induced crashes. IterPro repairs the corrupted process states on-the-fly upon occurrences of errors, enabling applications to continue their executions instead of being terminated. IterPro also exploits side effects introduced by induction variable based code optimization techniques to improve its recovery capability. To this end, two new code transformation passes are introduced to expose the side effects for resilience purposes. We evaluated IterPro with 4 scientific workloads as well as the NPB benchmarks suite. During their normal execution, IterPro incurs almost zero runtime overhead and a small, fixed 27MB memory overhead. Meanwhile, IterPro can recover on an average 83.55% of crash-causing errors within dozens of milliseconds with negligible downtime. With such an effective recovery mechanism, IterPro could tremendously mitigate the overheads and resource requirements of the resilience subsystem in future extreme-scale systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
