Compute, Time and Energy Characterization of Encoder-Decoder Networks
with Automatic Mixed Precision Training

Compute, Time and Energy Characterization of Encoder-Decoder Networks with Automatic Mixed Precision Training

18 August 2020

Michael Jones

Mark S. Veillette

Papers citing "Compute, Time and Energy Characterization of Encoder-Decoder Networks with Automatic Mixed Precision Training"

8 / 8 papers shown

Title
A review of radar-based nowcasting of precipitation and applicable machine learning techniques R. Prudden Samantha V. Adams D. Kangin Nial H. Robinson Suman V. Ravuri S. Mohamed A. Arribas AI4Cl OffRL 57 45 0 11 May 2020
Machine Learning for Precipitation Nowcasting from Radar Images Shreya Agrawal Luke Barrington Carla Bromberg J. Burge Cenk Gazen Jason Hickey AI4Cl 39 223 0 11 Dec 2019
Distributed Deep Learning for Precipitation Nowcasting S. Samsi Christopher J. Mattioli Mark S. Veillette 43 23 0 28 Aug 2019
Energy and Policy Considerations for Deep Learning in NLP Emma Strubell Ananya Ganesh Andrew McCallum 31 2,633 0 05 Jun 2019
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric Richard Y. Zhang Phillip Isola Alexei A. Efros Eli Shechtman Oliver Wang EGVM 182 11,610 0 11 Jan 2018
Mixed Precision Training Paulius Micikevicius Sharan Narang Jonah Alben G. Diamos Erich Elsen ... Boris Ginsburg Michael Houston Oleksii Kuchaiev Ganesh Venkatesh Hao Wu 116 1,779 0 10 Oct 2017
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 423 7,952 0 13 Jun 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 865 76,547 0 18 May 2015