Working Paper Article Version 1 This version is not peer-reviewed

Exploring Energy-Efficient Ternary Inexact Multipliers Using CNT Transistors

Version 1 : Received: 5 March 2020 / Approved: 7 March 2020 / Online: 7 March 2020 (02:53:54 CET)

A peer-reviewed article of this Preprint also exists.

Tabrizchi, S.; Panahi, A.; Sharifi, F.; Mahmoodi, H.; A. Badawy, A.-H. Energy-Efficient Ternary Multipliers Using CNT Transistors. Electronics 2020, 9, 643. Tabrizchi, S.; Panahi, A.; Sharifi, F.; Mahmoodi, H.; A. Badawy, A.-H. Energy-Efficient Ternary Multipliers Using CNT Transistors. Electronics 2020, 9, 643.

Journal reference: Electronics 2020, 9, 643
DOI: 10.3390/electronics9040643

Abstract

In recent decades, power consumption has become an essential factor in attracting the attention of integrated circuit (IC) designers. Multiple-valued logic (MVL) and approximate computing are some techniques that could be applied to integrated circuits to make power-efficient systems. By utilizing MVL-based circuits instead of binary logic, the information conveyed by digital signals increases, and this reduces the required interconnections and power consumption. On the other hand, approximate computing is a class of arithmetic computing used in systems where the accuracy of the computation can be traded-off for lower energy consumption. In this paper, we propose novel designs for exact and inexact ternary multipliers based on carbon-nanotube field-effect transistors (CNFETs). The unique characteristics of CNFETs make them a desirable alternative to MOSFETs. The simulations are conducted using Synopsys HSPICE. The proposed design is compared against existing ternary multipliers. The results show that the proposed exact multiplier reduces energy consumption by up to 6X. At the same time, the best inexact design improves energy efficiency by up to 35X compared to the latest state-of-the-art methods. Using the imprecise multipliers for image processing provides evidence that these proposed designs are a low-power system with an acceptable error.

Subject Areas

CNFETs; Approximate Computing; Multiple-Valued Logic

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