Computer Science ›› 2019, Vol. 46 ›› Issue (11A): 524-527.

• Interdiscipline & Application • Previous Articles     Next Articles

Parallel Algorithm Design for Assisted Diagnosis of Prostate Cancer

SU Qing-hua1, FU Jing-chao1, GU Han2,3, ZHANG Shan-shan2,3, LI Yi-fei2,3, JIANG Fang-zhou2,3, BAI Han-lin1, ZHAO Di2   

  1. (Information Engineering School,Beijing Wuzi University,Beijing 101149,China)1;
    (Institute of Computing Technology,Chinese Academy of Sciences,Beijing 100190,China)2;
    (Beijing University of Posts and Telecommunications,Beijing 100089,China)3
  • Online:2019-11-10 Published:2019-11-20

Abstract: In the contemporary era of high cancer,prostate cancer is a unique disease for men,and the incidence is increasing year by year.Convolutional neural networks have attracted much attention due to their powerful performance in the field of image recognition,and are also very suitable for computer-aided diagnosis.Training a convolutional neural network is time consuming because neural network models often contain a large number of parameters.How to accele-rate the training of neural networks has become a very important issue in the field of deep learning.To solve this problem,a multi-GPU parallel scheme is generally adopted.Among them,data synchronization performs better when the GPU performance is balanced.Therefore,this paper draws on the algorithm based on data parallel to accelerate the three-dimensional convolution network of prostate.

Key words: Convolutional network, Deep learning, Multi-GPU parallelism, Data parallelism, Neural network

CLC Number: 

  • G312
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