Hardware-Software Codesign of Accurate, Multiplier-free Deep Neural Networks

11 May 2017

Papers citing "Hardware-Software Codesign of Accurate, Multiplier-free Deep Neural Networks"

8 / 8 papers shown

Title
CoNLoCNN: Exploiting Correlation and Non-Uniform Quantization for Energy-Efficient Low-precision Deep Convolutional Neural Networks Muhammad Abdullah Hanif G. M. Sarda Alberto Marchisio Guido Masera Maurizio Martina Mohamed Bennai MQ 35 4 0 31 Jul 2022
Parallel Blockwise Knowledge Distillation for Deep Neural Network Compression Cody Blakeney Xiaomin Li Yan Yan Ziliang Zong 53 40 0 05 Dec 2020
Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights Shail Dave Riyadh Baghdadi Tony Nowatzki Sasikanth Avancha Aviral Shrivastava Baoxin Li 64 82 0 02 Jul 2020
ALERT: Accurate Learning for Energy and Timeliness Chengcheng Wan M. Santriaji E. Rogers H. Hoffmann Michael Maire Shan Lu AI4CE 48 40 0 31 Oct 2019
Robust and Computationally-Efficient Anomaly Detection using Powers-of-Two Networks Usama Muneeb Erdem Koyuncu Yasaman Keshtkarjahromi H. Seferoglu M. F. Erden Ahmet Enis Cetin 26 6 0 30 Oct 2019
A Resource-Efficient Embedded Iris Recognition System Using Fully Convolutional Networks Hokchhay Tann Heng Zhao Sherief Reda 11 10 0 08 Sep 2019
RxNN: A Framework for Evaluating Deep Neural Networks on Resistive Crossbars Shubham Jain Abhronil Sengupta Kaushik Roy A. Raghunathan 30 87 0 31 Aug 2018
Runtime Configurable Deep Neural Networks for Energy-Accuracy Trade-off Hokchhay Tann S. Hashemi R. I. Bahar Sherief Reda 34 72 0 19 Jul 2016