SkippyNN
Reza Hojabr, Kamyar Givaki, S. M. Reza Tayaranian, Parsa Esfahanian, Ahmad Khonsari, Dara Rahmati, M. Hassan Najafi · 2019
Employing convolutional neural networks (CNNs) in embedded devices seeks novel low-cost and energy efficient CNN accelerators. Stochastic computing (SC) is a promising low-cost alternative to conventional binary implementations of CNNs. Despite the low-cost advantage, SC-based arithmetic units suffer from prohibitive execution time due to processing long bit-streams. In particular, multiplication as the main operation in convolution computation, is an extremely time-consuming operation which hampers employing SC methods in designing embedded CNNs.