Combining Testing and Monitoring for Online Functional Guarantees in Imprecise Hardware Systems

结合测试和监控来保证不精确的硬件系统中的在线功能

• 批准号: 471837173
• 负责人: Professor Dr.-Ing. Görschwin Fey
• 金额: --
• 依托单位: Institut für Eingebettete Systeme E-13
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/471837173?language=en
• 关键词: Combining; Testing; Monitoring; Online; Functional

Two forces are shaping the design of new digital systems: variability and approximation. As technology scales, the variability of devices and interconnects increases dramatically due to intrinsic (e.g., unequal dopant concentrations) and extrinsic (e.g., temperature variations) factors. Furthermore, devices degrade over time -the so-called aging- which exacerbates the variability problem. To palliate these issues, new design methodologies proposed to accept an "imprecise" functionality at some parts of the design and during some periods of time. Thus, errors are becoming an integral part of the design flow. The "imprecise" functionality appears in two fundamentally different flavors: either it is due to the unavoidable variability of the technology which is addressed with additional logic -the so-called stochastic processing- or it is created by design to reduce area or energy consumption of the system -the so-called approximate processing. These two characteristics will play an essential role when considering future systems, e.g., enhancing the infrastructure for the Internet of Things (IoT) and creating multiprocessor systems for high-performance computing.Currently, it is not possible to quantify the accuracy-warranties of an imprecise processing system reliably at run time when it includes imprecise hardware subject to aging and environmental changes. Consequently, safely deploying adaptable systems that use functional approximation and that are implemented in new variability-prone technologies is difficult. Our main goal is to overcome this problem by developing new concepts for the first run-time diagnostic infrastructure for imprecise circuits that provides functional guarantees. We want to achieve this by combining new algorithms for generation and synthesis of stimuli-based testing tightly joined with new hardware building blocks for monitoring functionality of a system at run time. We will validate our design tools and methodology on a Vision-System-on-Chip.

两种力量正在塑造新的数字系统的设计：可变性和近似值。随着技术规模的扩大，器件和互连的可变性由于内在因素（例如，不均匀的掺杂浓度）和外在因素（例如，温度变化）而急剧增加。此外，设备会随着时间的推移而退化——即所谓的老化——这加剧了可变性问题。为了缓和这些问题，新的设计方法建议在设计的某些部分和某些时期接受“不精确”的功能。因此，错误正在成为设计流程的一个组成部分。“不精确”功能以两种根本不同的方式出现：要么是由于技术不可避免的可变性，这是通过额外的逻辑来解决的，即所谓的随机处理；要么是为了减少系统的面积或能耗而设计的，即所谓的近似处理。在考虑未来的系统时，这两个特征将发挥重要作用，例如，增强物联网（IoT）的基础设施和创建用于高性能计算的多处理器系统。目前，不可能在运行时可靠地量化不精确处理系统的准确性保证，因为它包含受老化和环境变化影响的不精确硬件。因此，安全部署使用函数逼近的适应性系统并在易变的新技术中实现是困难的。我们的主要目标是通过为提供功能保证的不精确电路开发第一个运行时诊断基础设施的新概念来克服这个问题。我们希望通过将生成和合成基于刺激的测试的新算法与用于监控系统运行时功能的新硬件构建块紧密结合来实现这一目标。我们将在片上视觉系统上验证我们的设计工具和方法。