Macroeconomics

Energy consumption

Multiplier (economics)

Power–delay product

Adder

Algorithm

Gas compressor

Voltage

Engineering

Embedded system

Economics

Computer science

Multiplication (music)

Very-large-scale integration

Mechanical engineering

Transistor

Transistor count

Mathematics

Image (mathematics)

Logic gate

Electronic engineering

Artificial intelligence

Combinatorics

CMOS

Arithmetic

Electrical engineering

IEEE Transactions on Circuits and Systems I Regular Papers

Approximate computing is an emerging approach for reducing the energy consumption and design complexity in many applications where accuracy is not a crucial necessity. In this study, ultra-efficient imprecise 4:2 compressor and multiplier circuits as the building blocks of the approximate computing systems are proposed. The proposed compressor uses only one majority gate which is different from the conventional design methods using AND - OR and XOR logics. Furthermore, the majority gate is the fundamental logic block in many of the emerging majority-friendly nanotechnologies such as quantum-dot cellular automata (QCA) and single-electron transistor (SET). The proposed circuits are designed using FinFET as a current industrial technology and are simulated with HSPICE at 7nm technology node. The results indicate that our imprecise compressor is superior to its previous counterparts in terms of delay, power consumption, power delay product (PDP) and area, and improves these parameters on average by 32%, 68%, 78%, and 66%, respectively. In addition, the proposed efficient approximate multiplier is utilized in image multiplying as an important image processing application. The HSPICE and MATLAB simulations indicate that the proposed inexact multiplier provides a significant compromise between accuracy and design efficiency for approximate computing.

A Majority-Based Imprecise Multiplier for Ultra-Efficient Approximate Image Multiplication