QuAd: Design and analysis of Quality-area optimal Low-Latency approximate Adders

Approximate circuits exploit error resilience property of applications to tradeoff computation quality (accuracy) for gaining advantage in terms of performance, power, and/or area. While state-of-the-art low-latency approximate adders provide an accuracy-area-latency configurable design space, the selection of a particular configuration from the design space is still manually done. In this paper, we analytically analyze different structural properties of low-latency approximate adders to formulate a new adder model, Quality-area optimal Low-Latency approximate Adder (QuAd). It provides an increased design space as compared to state-of-the-art, providing design points that require less logic area for the same accuracy, as compared to state-of-the-art approximate adders. Furthermore, based upon our mathematical analysis, we show that, provided a latency constraint, an adder configuration with the highest quality and lowest area requirement can effortlessly be selected from the whole design space of QuAd adder model, without requiring any optimization strategy or numerical simulation. Our experimental results validate the developed model and also the quality-area optimality of our optimal QuAd adder configuration. For functional verification and prototyping, we have used a Xilinx Virtex-6 FPGA. RTL/behavioral models and MATLAB equivalent scripts, of our proposed adder model are made open source, to facilitate further research and development.