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A Reconfigurable Architecture with Sequential Logic-Based Stochastic Computing

机译:具有顺序逻辑的随机计算的可重构架构

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Computations based on stochastic bit streams have several advantages compared to deterministic binary radix computations, including low power consumption, low hardware cost, high fault tolerance, and skew tolerance. To take advantage of this computing technique, previous work proposed a combinational logicbased reconfigurable architecture to perform complex arithmetic operations on stochastic streams of bits. The long execution time and the cost of converting between binary and stochastic representations, however, make the stochastic architectures less energy efficient than the deterministic binary implementations. This article introduces a methodology for synthesizing a given target function stochastically using finite-state machines (FSMs), and enhances and extends the reconfigurable architecture using sequential logic. Compared to the previous approach, the proposed reconfigurable architecture can save hardware area and energy consumption by up to 30% and 40%, respectively, while achieving a higher processing speed. Both stochastic reconfigurable architectures are much more tolerant of soft errors (bit flips) than the deterministic binary radix implementations, and their fault tolerance scales gracefully to very large numbers of errors.
机译:与确定性二进制基因克计算相比,基于随机比特流的计算具有若干优点,包括低功耗,低硬件成本,高容错容差和歪曲容差。为了利用这种计算技术,之前的工作提出了一种组合逻辑可重构的可重新配置架构,用于对随机数据流进行复杂的算术运算。然而,长的执行时间和转换二进制和随机表示之间的成本使随机架构比确定性二进制实现更少能量效率。本文介绍了一种用于使用有限状态机(FSMS)随机合成给定目标功能的方法,并使用顺序逻辑增强和扩展可重新配置的架构。与先前的方法相比,所提出的可重构架构可以分别将硬件区域和能量消耗节省高达30%和40%,同时实现更高的处理速度。两个随机可重构架构的耐受性比确定性二进制基因克实现更容许软错误(位翻转),并且它们的容错率优雅地缩放到非常大量的错误。

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