90 citations · 229 across the 24 of their papers we have counts for
Showing 2023Show all
3 papers · 1 filter
cs.LG2023★ 23 cited
Efficient N:M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design
Chao Fang, Wei Sun, Aojun Zhou +1
Sparse training is one of the promising techniques to reduce the computational cost of DNNs while retaining high accuracy. In particular, N:M fine-grained structured sparsity, wher…
cs.AR2023★ 16 cited
A Precision-Scalable RISC-V DNN Processor with On-Device Learning Capability at the Extreme Edge
Longwei Huang, Chao Fang, Qiong Li +2
Extreme edge platforms, such as in-vehicle smart devices, require efficient deployment of quantized deep neural networks (DNNs) to enable intelligent applications with limited amou…
cs.AR2023★ 10 cited
PDPU: An Open-Source Posit Dot-Product Unit for Deep Learning Applications
Qiong Li, Chao Fang, Zhongfeng Wang
Posit has been a promising alternative to the IEEE-754 floating point format for deep learning applications due to its better trade-off between dynamic range and accuracy. However,…