16 citations · 26 across the 3 of their papers we have counts for
3 papers
cs.AR2025
Enable Lightweight and Precision-Scalable Posit/IEEE-754 Arithmetic in RISC-V Cores for Transprecision Computing
Qiong Li, Chao Fang, Longwei Huang +2
While posit format offers superior dynamic range and accuracy for transprecision computing, its adoption in RISC-V processors is hindered by the lack of a unified solution for ligh…
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,…