Fault-tolerant in-memory crossbar computing using quantified constraint solving

Alvaro Velasquez, Sumit Kumar Jha
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引用次数: 13

Abstract

There has been a surge of interest in the effective storage and computation of data using nanoscale crossbars. In this paper, we present a new method for automating the design of fault-tolerant crossbars that can effectively compute Boolean formula. Our approach leverages recent advances in Satisfiability Modulo Theories (SMT) solving for quantified bit-vector formula (QBVF). We demonstrate that our method is well-suited for fault-tolerant computation and can perform Boolean computations despite stuck-open and stuck-closed interconnect defects as well as wire faults. We employ our framework to generate various arithmetic and logical circuits that compute correctly despite the presence of stuck-at faults as well as broken wires.
基于量化约束求解的容错内存交叉计算
人们对利用纳米交叉棒有效地存储和计算数据产生了浓厚的兴趣。本文提出了一种能有效计算布尔公式的容错横杆的自动化设计方法。我们的方法利用了可满足模理论(SMT)解决量化位矢量公式(QBVF)的最新进展。我们证明了我们的方法非常适合于容错计算,并且可以在卡开和卡闭互连缺陷以及线路故障的情况下执行布尔计算。我们使用我们的框架来生成各种算术和逻辑电路,尽管存在卡滞故障和断线,但它们仍能正确计算。
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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