An Approximate Radix-4 Booth Multiplication Circuit Design

Abstract

Many modern applications, such as object recognition using deep neural networks, require extremely large numbers of multiplications, but can sacrifice accuracy in order to achieve lower power usage and faster operation. This thesis proposes a new approximate multiplier design based on radix-4 Booth encod- ing. The key novel aspect of the proposed design is that approximate circuits are designed to create intermediate terms, which are then used as the common inputs to almost all of the logic within one entire row of a partial product array, resulting in a multi-level logic circuit implementation with extremely low delay and power usage characteristics. The proposed 8-bit (16-bit) design improves the power delay product by 17.1% to 30.3% (88.9% to 96.4%) over the previous best designs. By using accurate, approximated, and truncated regions, a wide range of approximate multiplier designs with different error characteristics are possible. Using normalized mean error distance and relative error distance metrics, simulations using synthesized circuits are used to show that the proposed designs have significantly improved power/accuracy tradeoffs over the previous best designs.