A Hierarchical and Reconfigurable Process Element Design for Quantized Neural Networks

Convolution neural networks are very popular for various applications. However, data size and accuracy are the two major concerns to perform efficient and effective computations. In conventional CNN models, 32bits data are frequently used to maintain high accuracy. However, performing a bunch of 32bits multiply-and-accumulate (MAC) operations causes significant computing efforts as well as power c...