OPACT: Optimization of Approximate Compressor Tree for Approximate Multiplier

Weihua Xiao, Cheng Zhuo, Weikang Qian
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引用次数: 1

Abstract

Approximate multipliers have attracted significant attention of researchers for designing low-power systems. The most area-consuming part of a multiplier is its compressor tree (CT). Hence, the prior works proposed various approximate compressors to reduce the area of the CT. However, the compression strategy for the approximate compressors has not been systematically studied: Most of the prior works apply their ad hoc strategies to arrange approximate compressors. In this work, we propose OPACT, a method for optimizing approximate compressor tree for approximate multiplier. An integer linear programming problem is first formulated to co-optimize CT's area and error. Moreover, since different connection orders of the approximate compressors can affect the error of an approximate multiplier, we formulate another mixed-integer programming problem for optimizing the connection order. The experimental results showed that OPACT can produce approximate multipliers with an average reduction of 24.4% and 8.4% in power-delay product and mean error distance, respectively, compared to the best existing designs with the same types of approximate compressors used.
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近似乘法器的近似压缩树优化
近似乘法器在设计低功耗系统方面引起了研究人员的极大关注。乘法器最消耗面积的部分是它的压缩树(CT)。因此,前人提出了各种近似压缩器来减小CT的面积。然而,对于近似压缩器的压缩策略还没有系统的研究,前人的研究大多是采用他们的临时策略来布置近似压缩器。在这项工作中,我们提出了一种优化近似乘法器的近似压缩树的方法OPACT。首先建立了一个整数线性规划问题,以共同优化CT的面积和误差。此外,由于近似压缩器的不同连接顺序会影响近似乘法器的误差,我们制定了另一个混合整数规划问题来优化连接顺序。实验结果表明,与现有的最佳设计相比,使用相同类型的近似压缩器,OPACT可以产生近似乘法器,其功率延迟积和平均误差距离分别平均降低24.4%和8.4%。
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