Parallel BP Neural Network on Single-chip Cloud Computer

Neural network has been a clear focus in machine learning area. Back propagation (BP) method is frequently used in neural network training. In this work we paralleled BP neural network on Single-Chip Cloud Computer (SCC), an experimental processor created by Intel Labs, and analyzed multiple metrics under different configurations. We also varied the number of neurons (nodes) in the hidden layer of the BP neural networks and studied the impact. The experiment results show that a better performance can be obtained with SCC, especially when there are more nodes in the hidden layer of BP neural network. A low voltage and frequency configuration contributes to a low power per speedup. What is more, a medium voltage and frequency configuration contributes to both a low energy consumption and energy-delay product.