%0 Journal Article %1 Oh20041311 %A Oh, Kyoung-Su %A Jung, Keechul %D 2004 %J Pattern Recognition %K ma-zehe neuralnet %N 6 %P 1311 - 1314 %R http://dx.doi.org/10.1016/j.patcog.2004.01.013 %T GPU implementation of neural networks %U http://www.sciencedirect.com/science/article/pii/S0031320304000524 %V 37 %X 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.

@article{Oh20041311, 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. }, added-at = {2016-11-14T16:50:29.000+0100}, author = {Oh, Kyoung-Su and Jung, Keechul}, biburl = {https://www.bibsonomy.org/bibtex/28a406fddcb2de43dbccb51524a825f76/albinzehe}, description = {GPU implementation of neural networks}, doi = {http://dx.doi.org/10.1016/j.patcog.2004.01.013}, interhash = {44a9b4d1c8f3458e56670e6597c687ee}, intrahash = {8a406fddcb2de43dbccb51524a825f76}, issn = {0031-3203}, journal = {Pattern Recognition }, keywords = {ma-zehe neuralnet}, number = 6, pages = {1311 - 1314}, timestamp = {2016-11-14T16:50:52.000+0100}, title = {GPU implementation of neural networks }, url = {http://www.sciencedirect.com/science/article/pii/S0031320304000524}, volume = 37, year = 2004 }