Energy-Efficient Logarithmic Square Rooter for Error-Resilient Applications

Abstract

Approximate computing is an emerging computing technique for designing energy- and resource-efficient arithmetic circuits for error-resilient applications. Square root (SQR) computation is a fundamental and complex operation in various signal/image processing tasks. It demands high resource and energy consumption, making the square-rooter a crucial design element. This brief proposes a low-complexity logarithmic-based energy-efficient approximate square rooter (LESQ) for computing integer SQR using simple addition and shift operations. A partial error compensation scheme is also suggested for improved accuracy. The proposed approximate square rooter also enables various accuracy configurable modes to tradeoff error with hardware efficiency for targeted application requirements. LESQ achieves energy- and area-delay savings of up to 80% and 60%, respectively, compared to an accurate array-based square-rooter design. The proposed approximate design is tested on error-tolerant applications, such as image processing and amplitude modulation (AM) communication system.