Dynamic point stochastic rounding algorithm for limited precision arithmetic in Deep Belief Network training

• Main Authors: Essam, M., Tang, T.B., Ho, E.T.W., Chen, H.
• Format: Article
• Published: IEEE Computer Society 2017
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028585216&doi=10.1109%2fNER.2017.8008430&partnerID=40&md5=3d565633d6b0ee148b8349a9b15f1d76; http://eprints.utp.edu.my/20033/
• Institution: Universiti Teknologi Petronas

This paper reports how to train a Deep Belief Network (DBN) using only 8-bit fixed-point parameters. We propose a dynamic-point stochastic rounding algorithm that provides enhanced results compared to the existing stochastic rounding. We show that by using a variable scaling factor, the fixed-point...