Rebooting Computing: The Challenges for Test and Reliability

A. Bosio, Ian O’Connor, G. Rodrigues, F. Kastensmidt, E. Vatajelu, G. D. Natale, L. Anghel, S. Nagarajan, M. Fieback, S. Hamdioui
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引用次数: 11

Abstract

Today's computer architectures and semiconductor technologies are facing major challenges making them incapable to deliver the required features (such as computer efficiency) for emerging applications. Alternative architectures are being under investigation in order to continue deliver sustainable benefits for the foreseeable future society at affordable cost. These architectures are not only changing the traditional computing paradigm (e.g., in terms of programming models, compilers, circuit design), but also setting up new challenges and directions on the way these architectures should be tested to guarantee the required quality and reliability levels. This paper highlights the major open questions regarding test and reliability of three emerging computing paradigms being approximate computing, computation-in-memory and neuromorphic computing.
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重新启动计算:测试和可靠性的挑战
今天的计算机体系结构和半导体技术正面临着重大挑战,使它们无法为新兴应用程序提供所需的功能(例如计算机效率)。为了以可承受的成本继续为可预见的未来社会提供可持续的利益,替代架构正在研究中。这些体系结构不仅改变了传统的计算范式(例如,在编程模型、编译器、电路设计方面),而且对这些体系结构的测试方式提出了新的挑战和方向,以保证所需的质量和可靠性水平。本文重点介绍了近似计算、内存计算和神经形态计算这三种新兴计算范式在测试和可靠性方面的主要开放性问题。
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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Rebooting Computing: The Challenges for Test and Reliability A Comprehensive Evaluation of the Effects of Input Data on the Resilience of GPU Applications On the Criticality of Caches in Fault-Tolerant Processors for Space On-line Testing for Autonomous Systems driven by RISC-V Processor Design Verification Understanding of GPU Architectural Vulnerability for Deep Learning Workloads
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