SAADI: a scalable accuracy approximate divider for dynamic energy-quality scaling

Setareh Behroozi, Jingjie Li, Jackson Melchert, Younghyun Kim

Abstract: Approximate computing can significantly improve the energy efficiency of arithmetic operations in error-resilient applications. In this paper, we propose an approximate divider design that facilitates dynamic energy-quality scaling. Conventional approximate dividers lack runtime energy-quality scalability, which is the key to maximizing the energy efficiency while meeting dynamically varying accuracy requirements. Our divider design, named SAADI, makes an approximation to the reciprocal of the divisor in an incremental manner, thus the division speed and energy efficiency can be dynamically traded for accuracy by controlling the number of iterations. For the approximate 8-bit division of 32-bit/16-bit division, the average accuracy of SAADI can be adjusted in between 92.5% and 99.0% by varying latency up to 7x. We evaluate the accuracy and energy consumption of SAADI for various design parameters and demonstrate its efficacy for low-power signal processing applications.