Design of low power approximate floating‐point adders

Abstract

SummaryDue to the increasing demands for more power in data intensive computing, low power design methodologies play a very important role in these systems. For noncritical data, the approximate computing that significantly reduces the power can be used. In this paper, an approximate floating‐point adder is proposed by designing an inexact mantissa adder and exponent subtractor. The results indicate that the power consumption and delay of the proposed approximate floating‐point adder have been decreased by 37% and 62% compared with the IEEE‐754 single‐precision floating‐point (FP) adder. Furthermore, compared with a state‐of‐the‐art inexact floating‐point adder, the proposed method provides an improvement of 7% and 21% in terms of the power consumption and delay. In addition, the proposed floating‐point adder has been investigated in terms of error, and the mean error of the proposed floating‐point adder at worst is about 55% less than that of another approximate floating‐point adder considered in this work. High dynamic range (HDR) images are processed using the proposed approximate floating‐point adders to show the performance of the proposed adder. The results show that, on average, peak signal‐to‐noise ratio increased by 9.6 and 18.64 dB, which may be achieved by utilizing the proposed floating‐point adder.