GPU implementation of neural networks
- Authors
- Oh, KS; Jung, K
- Issue Date
- Jun-2004
- Publisher
- PERGAMON-ELSEVIER SCIENCE LTD
- Keywords
- graphics processing unit(GPU); neural network(NN); multi-layer perceptron; text detection
- Citation
- PATTERN RECOGNITION, v.37, no.6, pp.1311 - 1314
- Journal Title
- PATTERN RECOGNITION
- Volume
- 37
- Number
- 6
- Start Page
- 1311
- End Page
- 1314
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/19989
- DOI
- 10.1016/j.patcog.2004.01.013
- ISSN
- 0031-3203
- 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. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
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