GPU implementation of neural networks |
| |
Authors: | Kyoung-Su Oh Keechul Jung |
| |
Affiliation: | School of Media, College of Information Science, Soongsil University, 1, SangDo-Dong, DongJak-Gu, Seoul, 156-743, Republic of Korea |
| |
Abstract: | Graphics processing unit (GPU) is used for a faster artificial neural network. It is used to implement the matrix multiplication of a neural network to enhance the time performance of a text detection system. Preliminary results produced a 20-fold performance enhancement using an ATI RADEON 9700 PRO board. The parallelism of a GPU is fully utilized by accumulating a lot of input feature vectors and weight vectors, then converting the many inner-product operations into one matrix operation. Further research areas include benchmarking the performance with various hardware and GPU-aware learning algorithms. |
| |
Keywords: | Graphics processing unit(GPU) Neural network(NN) Multi-layer perceptron Text detection |
本文献已被 ScienceDirect 等数据库收录! |
|