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Systematic synthesis of approximate adders and multipliers with accurate error calculations

机译:近似加法器和乘法器的系统综合以及精确的误差计算

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In this study, we perform logic synthesis and area optimization of approximate ripple-carry adders and Wallace-tree multipliers with a given error constraint. We first implement approximate 1-bit adders having different error rates as building blocks of the proposed multi-bit adders and multipliers. In implementations, we exploit offsetting errors in carry and sum outputs of the adders. Also we take into account the probability of occurrence of input assignments. Using the implemented 1-bit adders, we systematically synthesize multi-bit adders and multipliers proceeding from the least to the most significant bits. We design the ripple-carry adders such that their successive 1-bit approximate adders cannot produce build-up errors. We design the Wallace-tree multipliers by considering the fact that their building blocks of 1-bit adders might have different probabilities of occurrence for different input assignments. As a result, the proposed adders and multipliers, implemented using the Cadence Genus tool with TSMC 0.18 mu m CMOS technology, offer in average a 25% smaller circuit area, and correspondingly power consumption, compared to the circuits proposed in the literature by satisfying the same error constraint. We also evaluate the adders and multipliers in image processing applications as well as within artificial neural networks.
机译:在这项研究中,我们在给定误差约束下,对近似纹波进位加法器和华莱士树乘法器进行逻辑综合和面积优化。我们首先实现具有不同错误率的近似1位加法器,作为提出的多位加法器和乘法器的构建块。在实现中,我们利用加法器的进位和求和输出中的偏移误差。我们还考虑了输入分配发生的可能性。使用已实现的1位加法器,我们系统地综合了从最低位到最高有效位的多位加法器和乘法器。我们设计脉动进位加法器,使其连续的1位近似加法器不会产生累积误差。通过考虑以下事实来设计华莱士树乘法器:它们的1位加法器构建块对于不同的输入分配可能具有不同的发生概率。结果,与文献中提出的电路相比,采用Cadence Genus工具和TSMC 0.18μmCMOS技术实现的拟议加法器和乘法器与文献中提出的电路相比,平均电路面积小25%,相应地降低了功耗。相同的错误约束。我们还评估了图像处理应用以及人工神经网络中的加法器和乘法器。

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