A Novel FPGA Accelerator Design for Real-Time and Ultra-Low Power Deep Convolutional Neural Networks Compared With Titan X GPU

A Novel FPGA Accelerator Design for Real-Time and Ultra-Low Power Deep Convolutional Neural Networks Compared With Titan X GPU

Convolutional neural networks (CNNs) based deep learning algorithms require high data flow and computational intensity. For real-time industrial applications, they need to overcome challenges such as high data bandwidth requirement and power consumption on hardware platforms. In this work, we have a...

Full description

Bibliographic Details
Main Authors: Shuai Li, Yukui Luo, Kuangyuan Sun, Nandakishor Yadav, Kyuwon Ken Choi
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Deep neural network accelerator
FPGA
pipeline architecture
parallel computing
mixed fixed-point
object detection
Online Access:https://ieeexplore.ieee.org/document/9108269/

Internet

https://ieeexplore.ieee.org/document/9108269/

Similar Items