Comparison of Deep Learning in Neural Networks on CPU and GPU-based frameworks

被引：0
|
作者：
Aida-zade, Kamil [1 ]
Mustafayev, Elshan [2 ]
Rustamov, Samir [3 ]
机构：
[1] Baku State Univ, Baku, Azerbaijan
[2] Azerbaijan Natl Acad Sci, Inst Control Syst, Baku, Azerbaijan
[3] ADA Univ, Baku, Azerbaijan
来源：
2017 11TH IEEE INTERNATIONAL CONFERENCE ON APPLICATION OF INFORMATION AND COMMUNICATION TECHNOLOGIES (AICT 2017) | 2017年
关键词：
deep learning; digit recognition; GPU; CUDA; Tensorflow; MNIST;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In the work, the problem of training of deep neural networks on GPU and CPU-based frameworks is investigated. As a test problem, the MNIST Dataset was taken for recognition of handwritten digits. The results of deep learning are compared and analyzed in both frameworks for the current problem.
引用
收藏
页码：95 / 98
页数：4
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