SHF: Small: Software-Driven Hardware Resiliency

摩尔定律继续提供丰富的芯片设备，但它们越来越多地受到来自多个来源的失败的影响。硬件可靠性问题预计将无处不在，影响从嵌入式系统到高性能计算的各种市场。迫切需要研究以极低的面积、性能和功耗(不包括传统的基于冗余的解决方案)来解决这一问题。最近，研究人员提出了一种软件驱动的硬件可靠性解决方案，该解决方案仅处理软件可见并导致软件异常行为的设备故障。这项工作在以极低的成本检测大多数故障方面取得了相当成功的效果。不幸的是，一些硬件故障逃脱了建议的异常监视器的检测，导致静默数据损坏或SDC。剩下的几个SDC一直是软件驱动的硬件弹性方法的致命弱点，也是广泛采用的障碍。这项拟议的研究试图克服这一障碍。这项研究包括方法创新，可以在实际工作流程中确定易受SDC影响的应用站点，以及使用这些信息开发低成本检测和恢复技术以减轻SDC影响的弹性解决方案。它建立在原理调查者小组最近开发的弹性分析工具Relyzer的基础上。关键的见解是，Relyzer可以尝试确定哪些应用程序站点将产生相同的结果，而不是试图确定每个故障站点的结果。这使得能够修剪大量站点，并专注于每个等价类只有一个站点的故障注入，从而显著缩短恢复能力评估时间。除了提供SDC易受攻击指令的列表外，Relyzer还提供了大量有关它们易受攻击的原因的信息。这促使使用廉价的特定于应用程序的检测器来利用这些信息。然而，Relyzer在速度、准确性和通用性方面有几个限制，使其无法在实际工作流中使用。这项研究将首先开发新的技术来解决这些限制，并在工具中实现它们。其次，这项研究将探索系统技术，以开发实用的弹性解决方案，利用Relyzer暴露的丰富的故障传播信息。它将开发系统的低成本检测和恢复技术，在弹性和性能管理费用之间进行可量化的权衡，可以将其纳入实际应用的实际工作流程中。如果成功，这项工作将解决在满足摩尔定律表现对各种社会进步的期望方面的一个关键挑战。除了研究的好处，它还将为实际的全面应用弹性分析提供一个具体的工具，并将培养研究生。

Moore's law continues to provide abundant devices on chip, but they are increasingly subject to failures from many sources. The hardware reliability problem is expected to be pervasive, affecting markets from embedded systems to high performance computing. There is an urgent need for research to address this problem with extremely low overheads in area, performance, and power (precluding traditional redundancy based solutions). Recently, researchers have proposed a software-driven hardware reliability solution that handles only the device faults that become visible to software and cause anomalous software behavior. This line of work has been quite successful in detecting most faults at extremely low cost. Unfortunately, some hardware faults escape detection by the proposed anomaly monitors, resulting in silent data corruption or SDC. These remaining few SDCs have been the Achilles heel of the software-driven hardware resiliency approach and a hindrance to widespread adoption. The proposed research seeks to overcome this obstacle. The research includes methodological innovations that can determine application sites vulnerable to SDCs within a practical workflow and resiliency solution that uses this information to develop low cost detection and recovery techniques to mitigate the impact of SDCs. It builds on a recent resiliency analysis tool developed by the Principle Investigator's group called Relyzer. The key insight is that instead of trying to determine the outcome of each fault site, Relyzer can seek to determine which application sites will produce equivalent outcomes. This enables pruning a large number of sites and focusing on fault injections for just one site per equivalence class, resulting in significant reduction in resiliency evaluation time. In addition to providing a list of SDC vulnerable instructions, Relyzer also provides a wealth of information on why they are vulnerable. This motivates the use of inexpensive application-specific detectors that exploit this information. However, Relyzer has several limitations in speed, accuracy, and generality, precluding its use in a practical workflow. This research will first develop new techniques to address these limitations and to implement them in a tool. Second, this research will explore systematic techniques to develop practical resiliency solutions that exploit the wealth of fault-propagation information exposed by Relyzer. It will develop systematic low-cost detection and recovery techniques, with quantifiable tradeoffs between resiliency and performance overheads, that can be incorporated in a practical workflow for real applications. If successful, this work will address a key challenge in meeting the expectations of Moore's law performance for a wide variety of societal advances. Besides the research benefits, it will provide a concrete tool for practical full application resiliency analysis and will also train graduate students.