Booth Encoded Bit-Serial Multiply-Accumulate Units with Improved Area and Energy Efficiencies

Abstract

Bit-serial multiply-accumulate units (MACs) play a crucial role in various hardware accelerator applications, including deep learning, image processing, and signal processing. Despite the advantages of bit-serial MACs, such as a small footprint, full hardware utilization, and high frequency, their serial nature can lead to high latency and potentially compromised performance. This study investigates the potential of bit-serial solutions by applying Booth encoding to bit-serial multipliers within MACs to enhance area and power efficiencies. We present two types of bit-serial MACs based on radix-2 and radix-4 Booth encoding multipliers, respectively. Their performance is assessed through simulations and synthesis results, demonstrating the benefits of the proposed approach. The radix-4 Booth bit-serial MAC improves power and area efficiencies compared to the original bit-serial MAC. Operating at TSMC 90 nm and 150 MHz, our design exhibits a remarkable 96.39% reduction in area-power-product (APP). Moreover, the prototype verification on a Xilinx Kintex-7 FPGA proved successful. The proposed solution offers significant advantages in energy efficiency, area reduction, and APP, making it a promising candidate for next-generation hardware accelerators in offline inference, low-power devices, and other applications.