Energy-Efficient Approximate Squaring Hardware for Error-Resilient Digital Systems

In recent years, there has been a high demand for executing digital signal processing and machine learning applications on energy-constrained devices. Squaring is a vital arithmetic operation used in such applications. Hence, improving the energy efficiency of squaring is crucial. In this paper, a novel approximation method based on piecewise linear segmentation of the square function is proposed. An energy-efficient 32-bit approximate hardware for squaring was implemented using this method. The proposed hardware achieved a mean relative error of 0.43% and delivered up to 47% energy saving when compared with state-of-the-art approximate multipliers. The comparison also revealed that the proposed hardware is the most efficient design in terms of error-area-delay-power product.