SHF: Small: Collaborative Research: Using Identified Circuit Invariance for Online Error Detection

确保纳米级的可靠计算需要检测错误的机制。PI提出了开发有效的硬件技术的基础研究，以支持在线错误检测和制造测试，通过监测不变的关系。这些不变的关系自然地发生在数字逻辑的多个层次和多个时间周期中。违反这些关系表明发生了错误，无论是由于瞬时故障还是制造缺陷;因此在硬件中监视它们可以显着提高电路的可靠性。虽然存在用于错误检测的其他技术，但这种方法具有几个优点，包括显著降低功耗，没有高级信息要求，细粒度优化功能，以及提供潜在的强大诊断信息源。在这个项目中的一个关键挑战是有效地选择一组最佳的影响，包括在硬件中，这样，所需的可靠性，获得低开销。逻辑器件的可靠运行是持续推动更小更快电子电路的关键。如果不能保证由这些器件组成的系统的高可靠性，则不能完全实现由晶体管的快速缩放带来的性能和功率方面的任何益处。这项拟议中的研究是布朗大学和巴克内尔大学之间的合作。该项目涉及本科生，其中许多是妇女和代表性不足的少数民族。PI将利用该项目创造新的机会，让本科生接触研究，并开发推广讲习班，鼓励妇女和代表性不足的少数民族攻读计算机学位。

Ensuring reliable computation at the nanoscale requires mechanisms to detect errors. The PIs propose fundamental research for developing efficient hardware techniques to support online error detection and manufacturing test by monitoring invariant relationships. These invariant relationships naturally occur across multiple levels of digital logic and across multiple time cycles. Violations of these relationships indicate that errors have occurred, either because of transient faults or manufacturing defects; thus monitoring them in hardware can significantly improve circuit reliability. While other techniques exist for error detection, this approach has several advantages, including significantly lower power dissipation, no high-level information requirements, fine-grained optimization capabilities, and providing a potentially powerful source of diagnostic information. A key challenge in this project is the efficient selection of an optimal set of implications to include in the hardware, such that desired reliability is obtained with low overhead. Reliable operation of logic devices is key for the continued push for smaller and faster electronic circuits. Any benefit in performance and power brought forth by rapid scaling of transistors cannot be fully realized if high reliability cannot be guaranteed for systems composed of these devices. The proposed research is a collaborative effort between Brown and Bucknell Universities. The project involves undergraduate students, many of whom are women and under-represented minorities. The PIs will use this project to create new opportunities to expose undergraduates to research, and to develop outreach workshops to encourage women and under-represented minorities to pursue degrees in computing.