High Performance Implementation of 3D Convolutional Neural Networks on a GPU
Joint Authors
Zhang, Chunyuan
Lan, Qiang
Wang, Zelong
Wen, Mei
Wang, Yijie
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-08
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Convolutional neural networks have proven to be highly successful in applications such as image classification, object tracking, and many other tasks based on 2D inputs.
Recently, researchers have started to apply convolutional neural networks to video classification, which constitutes a 3D input and requires far larger amounts of memory and much more computation.
FFT based methods can reduce the amount of computation, but this generally comes at the cost of an increased memory requirement.
On the other hand, the Winograd Minimal Filtering Algorithm (WMFA) can reduce the number of operations required and thus can speed up the computation, without increasing the required memory.
This strategy was shown to be successful for 2D neural networks.
We implement the algorithm for 3D convolutional neural networks and apply it to a popular 3D convolutional neural network which is used to classify videos and compare it to cuDNN.
For our highly optimized implementation of the algorithm, we observe a twofold speedup for most of the 3D convolution layers of our test network compared to the cuDNN version.
American Psychological Association (APA)
Lan, Qiang& Wang, Zelong& Wen, Mei& Zhang, Chunyuan& Wang, Yijie. 2017. High Performance Implementation of 3D Convolutional Neural Networks on a GPU. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1141149
Modern Language Association (MLA)
Lan, Qiang…[et al.]. High Performance Implementation of 3D Convolutional Neural Networks on a GPU. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1141149
American Medical Association (AMA)
Lan, Qiang& Wang, Zelong& Wen, Mei& Zhang, Chunyuan& Wang, Yijie. High Performance Implementation of 3D Convolutional Neural Networks on a GPU. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1141149
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141149