乘数(经济学)
CMOS芯片
可重构性
计算机科学
气体压缩机
晶体管计数
高效能源利用
电子工程
晶体管
超大规模集成
电子线路
加法器
能源消耗
逻辑门
嵌入式系统
电气工程
算法
工程类
电压
经济
电信
宏观经济学
机械工程
作者
Nima Kavand,Armin Darjani,Shubham Rai,Akash Kumar
出处
期刊:IEEE Transactions on Circuits and Systems Ii-express Briefs
[Institute of Electrical and Electronics Engineers]
日期:2023-05-15
卷期号:70 (9): 3644-3648
被引量:22
标识
DOI:10.1109/tcsii.2023.3275983
摘要
The ever-increasing demand for low-power and area-efficient circuits for use in battery-powered devices and the CMOS scaling problems have attracted the attention of VLSI designers to beyond-CMOS technologies like Reconfigurable Field-Effect Transistors (RFETs). Improving the efficiency of multipliers is critical as the core component of many applications such as image processing and Machine Learning (ML). This brief proposes a compact and energy-efficient RFET-based architecture for the 4:2 compressor and Dadda multiplier, leveraging transistor-level reconfigurability and multi-input support of the RFET. Moreover, we propose a novel approximate 4:2 compressor based on efficient RFET logic cells to cater to the needs of error-resilient applications. Extensive circuit-level simulations with 14nm germanium nanowire (GeNW) RFET technology show that the proposed RFET-based exact multiplier improves the power consumption and power-delay product (PDP) by 65% and 45%, respectively, compared to the conventional CMOS-based counterpart in 14nm FinFET technology. Besides, we show that utilizing the proposed approximate compressor, the area and PDP of the multiplier reduce by 46% and 42%. The effectiveness of the approximate multiplier is evaluated in the image multiplication, and the average PSNR and SSIM values are 31.39 and 0.87, respectively.
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