Approximate adder with output correction for error tolerant applications and Gaussian distributed inputs
Approximate computing is emerging as a new paradigm to improve digital circuit performance by relaxing the requirement of performing exact calculations. Approximate adders rely on the idea that for uniformly distributed inputs, long carry propagation chains are rarely activated. Unfortunately, however, the above assumption on input signal statistics is not always verified; in this paper we focus on the case (often encountered in practical signal processing applications) when the inputs have a Gaussian distribution. We show that for Gaussian inputs the error probability of previously proposed approximate adders approaches 25% for low sigma values, which is much larger than the uniform case. On the basis of this analysis, we propose an approximate adder with a correction circuit that drastically reduces the error rate for Gaussian distributed operand s. In order to investigate the performance of our approach in a real application, simulated results for a simple audio processing system are reported. Implementation results in 65nm technology are also presented.
2016 IEEE International Symposium on Circuits and Systems (ISCAS)