Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for
DNNs on the Edge

Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge

6 August 2019

H. F. Langroudi

Zachariah Carmichael

Dhireesha Kudithipudi

Papers citing "Cheetah: Mixed Low-Precision Hardware & Software Co-Design Framework for DNNs on the Edge"

5 / 5 papers shown

Title
GSQ-Tuning: Group-Shared Exponents Integer in Fully Quantized Training for LLMs On-Device Fine-tuning Sifan Zhou Shuo Wang Zhihang Yuan Mingjia Shi Yuzhang Shang Dawei Yang ALM MQ 90 0 0 18 Feb 2025
AI Augmented Edge and Fog Computing: Trends and Challenges Shreshth Tuli Fatemeh Mirhakimi Samodha Pallewatta Syed Zawad G. Casale B. Javadi Feng Yan Rajkumar Buyya N. Jennings 21 56 0 01 Aug 2022
How Low Can We Go: Trading Memory for Error in Low-Precision Training Chengrun Yang Ziyang Wu Jerry Chee Christopher De Sa Madeleine Udell 18 2 0 17 Jun 2021
PositNN: Training Deep Neural Networks with Mixed Low-Precision Posit Gonçalo Raposo P. Tomás Nuno Roma MQ 42 19 0 30 Apr 2021
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 59 116 0 07 Jun 2018