SHF: Small: Software-Driven Hardware Resiliency

摩尔定律继续提供大量的芯片上器件，但它们越来越容易受到来自许多来源的故障的影响。预计硬件可靠性问题将普遍存在，影响从嵌入式系统到高性能计算的市场。迫切需要研究以在面积、性能和功率方面极低的开销（排除传统的基于冗余的解决方案）来解决这个问题。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异常软件行为的设备故障。这条工作线在以极低的成本检测大多数故障方面相当成功。不幸的是，一些硬件故障逃脱了异常监视器的检测，导致无声的数据损坏或SDC。这些剩余的少数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。这项研究旨在克服这一障碍。 该研究包括方法创新，可以在实际工作流程和弹性解决方案中确定易受SDC影响的应用程序站点，该解决方案使用此信息开发低成本检测和恢复技术，以减轻SDC的影响。 它建立在最近由首席研究员小组开发的弹性分析工具Relyzer的基础上。关键的见解是，Relyzer可以试图确定哪些应用程序站点将产生等效的结果，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的站点，并专注于每个等价类仅一个站点的故障注入，从而显著减少弹性评估时间。除了提供易受攻击的SDC指令列表外，Relyzer还提供了大量关于它们为何易受攻击的信息。这促使使用利用这些信息的廉价的特定于应用的检测器。然而，Relyzer在速度、准确性和通用性方面有一些限制，排除了它在实际工作流程中的使用。这项研究将首先开发新技术来解决这些限制，并将其应用到工具中。其次，本研究将探索系统的技术来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，在复原力和性能开销之间进行可量化的权衡，可将其纳入真实的应用程序的实际工作流程。如果成功，这项工作将解决一个关键的挑战，在满足摩尔定律的性能的期望，为各种各样的社会进步。除了研究的好处，它将提供一个具体的工具，实际的全面应用弹性分析，也将培养研究生。

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.