Accelerating of Artificial Neural Network Training by GPU with OpenCL Support
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    Abstract:

    The computation quantity in artificial neural network training will get more and more with the increase of neurons quantity, it is time-consuming for training a neural network with too many neurons. A method that accelerates artificial neural network training is to optimize the training algorithm, so as to reduce the computation quantity. Since there is too much matrix and vector computation in artificial neural network training algorithm, the optimized training algorithm implemented by OpenCL C language on GPU, compared to the conventional CPU-based implementation, the training speed will be increased a lot. Based on parallel computing ability of hardware, accelerating of artificial neural network training by GPU with OpenCL Support is researched in this paper.

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祝伟华,付先珺.支持OpenCL 的GPU 加速人工神经网络训练.计算机系统应用,2011,20(7):217-220

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  • Received:October 20,2010
  • Revised:December 04,2010
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