空间多比特瞬态故障的体系结构脆弱性因子计算

Mark Wilkening, Vilas Sridharan, Si Li, Fritz G. Previlon, S. Gurumurthi, D. Kaeli
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引用次数: 45

摘要

在现代微处理器中,可靠性是一个重要的设计约束,其中一个基本的可靠性挑战是与瞬态故障的影响作斗争。这需要广泛的分析,包括重要的故障建模,以允许架构师做出明智的可靠性权衡。最近的数据显示,多位瞬态故障变得越来越普遍,从180nm的静态随机存取存储器(SRAM)故障的0.5%增加到22nm的3.9%。预计这类故障在较小的技术节点中更为普遍。因此,对多比特暂态故障的影响进行精确建模对微处理器的设计过程越来越重要。体系结构脆弱性因子(AVF)分析是一种对单比特暂态故障影响进行建模的方法。在本文中,我们提出了一种计算空间多比特瞬态故障(mb - avf)的avf的方法,并提供了有助于减少这些故障影响的见解。首先,我们描述了一种新的多比特AVF分析方法,用于检测未校正错误(DUE),并展示了如何在性能模拟器中测量DUE mb -AVF。然后,我们扩展了我们的方法来测量静默数据损坏(SDC) mb - avf。我们发现mb - avf不能由单比特avf衍生。我们还发现,更大的故障模式具有更高的mb - avf。最后,我们提出了一个使用MB-AVF分析来优化处理器设计的案例研究,在GPU矢量寄存器文件中产生86%的SDC降低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Calculating Architectural Vulnerability Factors for Spatial Multi-Bit Transient Faults
Reliability is an important design constraint in modern microprocessors, and one of the fundamental reliability challenges is combating the effects of transient faults. This requires extensive analysis, including significant fault modelling allow architects to make informed reliability tradeoffs. Recent data shows that multi-bit transient faults are becoming more common, increasing from 0.5% of static random-access memory (SRAM) faults in 180nm to 3.9% in 22nm. Such faults are predicted to be even more prevalent in smaller technology nodes. Therefore, accurately modeling the effects of multi-bit transient faults is increasingly important to the microprocessor design process. Architecture vulnerability factor (AVF) analysis is a method to model the effects of single-bit transient faults. In this paper, we propose a method to calculate AVFs for spatial multibittransient faults (MB-AVFs) and provide insights that can help reduce the impact of these faults. First, we describe a novel multi-bit AVF analysis approach for detected uncorrected errors (DUEs) and show how to measure DUE MB-AVFs in a performance simulator. We then extend our approach to measure silent data corruption (SDC) MB-AVFs. We find that MB-AVFs are not derivable from single-bit AVFs. We also find that larger fault modes have higher MB-AVFs. Finally, we present a case study on using MB-AVF analysis to optimize processor design, yielding SDC reductions of 86% in a GPU vector register file.
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