Accurus: A Fast Convergence Technique for Accuracy Configurable Approximate Adder Circuits

Approximate computing techniques have paved new paths to get substantial improvement in speed and power efficiency by making a trade-off with the accuracy of computations in inherently error tolerant applications, like from image and video processing domains. The accuracy requirements of various applications can differ from each other. Even within a same application different computations can have different accuracy requirements which can vary over time and upon user requirements. Accuracy configurable arithmetic circuits are essential for these reasons. Such techniques proposed earlier in the literature (ACA) work by improving the accuracy over several pipeline stages. However, those techniques suffer from the drawback that the corrections being made in the initial pipeline stages are small in magnitude as they are performed from the least significant bit position. In this paper, we propose a new correction technique -Accurus wherein we start from the most significant bit resulting in fast convergence of the result towards the accurate one. We used our approximate adder circuit in a Gaussian Blur filter which is then applied to an image. After one stage of correction, we achieved a peak signal to noise ratio of 40.90 dB when compared with 25.59 dB obtained using the previous well-known technique (ACA).