Energy Efficient Approximate Multiplier Design: From A Cross-Layer Perspective

Approximate computing is an effective approach to enhance circuit performance and energy efficiency by deliberately sacrificing accuracy. Among various arithmetic units, multiplication is a widely used but possibly the most energy-consuming operation. Its approximate variants have received growing interests from both academia and industry. However, the accuracy and energy efficiency of these approximations can vary greatly depending on how and where they are introduced into the design. This talk will first review various approximation techniques for multiplier design, ranging from circuit- to algorithm-level approaches. Then, we will delve into the recent developments in cross-layer approximate multiplier design, which combines circuit-level customization and algorithm-level optimization. Such a cross-layer perspective can address the above concerns by linking the algorithm specification to the circuit details to achieve the desired energy efficiency. We will also present results from RTL implementations in comparison to the prior works, demonstrating that the cross-layer methodology can lead to almost an order of magnitude improvement in energy efficiency with minimal accuracy loss.