This study proposes two ultraefficient imprecise multipliers based on innovative 4:2 approximate compressor designs. The first proposed multiplier employs an ultracompact 8‐transistor 4:2 compressor to reduce the transistor count and energy dissipation. To improve the accuracy of the first proposed imprecise multiplier, the second multiplier also benefits from a semiaccurate 24‐transistor 4:2 approximate compressor for the high‐order bits. The 7‐nm fin field‐effect transistor (FinFET) technology, as one of the leading commercial technologies, is utilized to simulate the proposed multipliers in the environment. The simulation results indicate that the proposed imprecise multipliers show significant improvements regarding transistor count, delay, power, and power‐delay product as compared to their state‐of‐the‐art imprecise and exact counterparts. Along with the superior hardware efficiency, the MATLAB simulations demonstrate that the proposed multipliers also provide reasonable levels of accuracy. Moreover, a figure of merit (FOM) considering hardware efficiency and output quality is considered in order to evaluate the multipliers comprehensively. The FOM simulation results indicate that the proposed imprecise multipliers make a significant trade‐off between hardware efficiency and quality for approximate‐computing applications dealing with image multiplication.

中文翻译：

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基于创新的4：2近似压缩器的超高效不精确乘法器

这项研究基于创新的4：2近似压缩机设计，提出了两个超高效不精确乘法器。提出的第一个乘法器采用超紧凑型8晶体管4：2压缩器，以减少晶体管数量和能量消耗。为了提高第一个提出的不精确乘法器的精度，第二个乘法器还受益于半精确的24晶体管4：2高位比特近似压缩器。作为领先的商业技术之一，7纳米鳍式场效应晶体管（FinFET）技术被用于模拟半导体中建议的乘法器。环境。仿真结果表明，与最新的不精确乘法器和精确对等乘法器相比，所提出的不精确乘法器在晶体管数量，延迟，功率和功率延迟乘积方面显示出显着改进。除了出色的硬件效率外，MATLAB仿真还表明，所提出的乘法器还提供了合理的精度水平。此外，为了综合评估乘数，考虑了考虑硬件效率和输出质量的品质因数（FOM）。FOM仿真结果表明，所提出的不精确乘法器在处理图像乘法的近似计算应用程序的硬件效率和质量之间做出了重大折衷。