15 citations · 15 across the 1 of their papers we have counts for
3 papers
cs.DC2019
A Survey of FPGA Based Deep Learning Accelerators: Challenges and Opportunities
Teng Wang, Chao Wang, Xuehai Zhou +1
With the rapid development of in-depth learning, neural network and deep learning algorithms have been widely used in various fields, e.g., image, video and voice processing. Howev…
cs.AR2017★ 15 cited
Reconfigurable Hardware Accelerators: Opportunities, Trends, and Challenges
Chao Wang, Wenqi Lou, Lei Gong +5
With the emerging big data applications of Machine Learning, Speech Recognition, Artificial Intelligence, and DNA Sequencing in recent years, computer architecture research communi…
cs.LG2016
DLAU: A Scalable Deep Learning Accelerator Unit on FPGA
Chao Wang, Qi Yu, Lei Gong +3
As the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems. However, the size of the networks becomes increasingly large…