Accuracy-Adaptive Spintronic Adder for Image Processing Applications
Abdolah Amirany, Gavin Epperson, Ahmad Patooghy, Ramin Rajaei
Abstract
Approximate computing (AC) is a recently emerged computing paradigm that can trade in accuracy for power, area, and delay in accuracy-insensitive applications, such as image processing. Magnetic tunnel junction (MTJ) cells can further these AC advancements as a result of their near-zero current leakage. In addition, due to the non-volatility of MTJs, an MTJ-based circuit can switch into a completely OFF state during idle cycles for further power savings without loss of data or the need for extra components. In this article, two novel MTJ-based approximate full-adder circuits are proposed and evaluated. The proposed 1 bit adder circuits are then extended to an 8 bit accuracy-adaptive adder that dynamically adjusts the level of accuracy as needed. For evaluations, we have employed the proposed accuracy-adaptive adder in the implementation of a Gaussian image processing filter. We have observed that, at the expense of a tolerable loss of accuracy, the proposed accuracy-adaptive adder offers up to 47% and 94% improvements in power and performance, respectively, when compared to its conventional accurate counterparts.