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

页码：95 / 98

页数：4

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