The Effect of High Performance Computer on Deep Learning: A Face Expression Recognition Case

In this paper, the facial expression recognition(FER) application is achieved by integrating Machine Learning and High Performance Computing (HPC). The convolutional neural network(CNN) will be trained utilizing the XSEDE high-performance computing resources. To observe the performance of HPC, CNN model has been trained with different values of parameters and their training times are provided. Compared to an ordinary computer, HPC with CPU and Google Colaboratory with GPU, this research explores the highest work efficiency of HPC with GPU with respect to operating time.