Comparative Evaluation between Carry Prediction and Sign Error Correction in Approximate Addition

This paper conducts a comparative evaluation of two schemes for approximate adders: sign error correction and carry prediction. Focusing on deep neural network (DNN) applications as targets, the study investigates which scheme is the preferred choice in the IoT era. Simulation results, including logic circuit synthesis, reveal that the two schemes perform similarly, with the predicting scheme showing a slight advantage.