Challenges of Reliability Assessment and Enhancement in Autonomous Systems

M. Jenihhin, M. Reorda, A. Balakrishnan, D. Alexandrescu
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引用次数: 6

Abstract

The gigantic complexity and heterogeneity of today's advanced cyber-physical systems and systems of systems is multiplied by the use of avant-garde computing architectures to employ artificial intelligence based autonomy in the system. Here, the overall system's reliability comes along with requirements for fail-safe, fail-operational modes specific to the target applications of the autonomous system and adopted HW architectures. The paper makes an overview of reliability challenges for intelligence implementation in autonomous systems enabled by HW backbones such as neuromorphic architectures, approximate computing architectures, GPUs, tensor processing units (TPUs) and SoC FPGAs.
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自主系统可靠性评估与增强的挑战
当今先进的网络物理系统和系统的系统的巨大复杂性和异质性通过使用前卫的计算架构在系统中采用基于人工智能的自主性而成倍增加。在这里,整个系统的可靠性取决于自动系统的目标应用和采用的硬件架构对故障安全、故障操作模式的要求。本文概述了由硬件骨干(如神经形态架构、近似计算架构、gpu、张量处理单元(tpu)和SoC fpga)支持的自主系统中智能实现的可靠性挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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