A high-performance FPGA architecture for restricted boltzmann machines

Abstract

Despite the popularity and success of neural networks in research, the number of resulting commercial or industrial applications have been limited. A primary cause of this lack of adoption is due to the fact that neural networks are usually implemented as software running on general-purpose processors. Algorithms to implement a neural network in software are typically O(n2) problems -- as a result, neural networks are unable to provide the performance and scalability required in non-academic settings.