Name
Abstract | ||
|---|---|---|
In recent years, convolutional neural network (CNN) has made a breakthrough development and been widely used in various fields, such as image recognition, target classification and natural language processing. However, with the continuous development of CNN, the complexity of CNN is gradually increasing. The ordinary hardware processors cannot meet the speed requirements of CNN. The hardware platform about CNN based on FPGA has gradually become the focus of research because of its parallel computing advantages. However, it is difficult and not friendly to implement CNN on FPGA for software developers. In this paper, we propose a FPGA-Cloud architecture for CNN. We implement CNN platform based on FPGA, and deploy the platform in the cloud. CNN resources based on FPGA can be utilized by local users through the network, which is language-friendly for software developers in hardware development and satisfies the user's requirement for CNN processing task. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/APCC.2018.8633447 | APCC |
Keywords | Field | DocType |
Cloud computing,Field programmable gate arrays,Servers,Computer architecture,Hardware,Control systems,Training | Computer architecture,Architecture,Computer science,Convolutional neural network,Server,Field-programmable gate array,Real-time computing,Software,Control system,Cloud architecture,Cloud computing | Conference |
ISBN | Citations | PageRank |
978-1-5386-6928-0 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guangju Wei | 1 | 0 | 0.34 |
| yanzhao hou | 2 | 2 | 2.46 |
| Zhao Zhao | 3 | 5 | 2.26 |
| Qimei Cui | 4 | 642 | 79.84 |
| gang deng | 5 | 3 | 2.39 |
| Xiaofeng Tao | 6 | 1033 | 140.26 |