Robust Large-Scale Convolution through Stochastic-Based Processing Without Multipliers

Large-scale discrete convolution, well-known to be computationally intensive, is a fundamental algorithmic building block in many computer vision and artificial intelligence applications. This work presents a novel stochastic-based hardware architecture and design that computes discrete convolution based on the widely-used convolution theorem. Our approach has three advantages. First, it can achie...