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Mixed Precision Training

Mixed Precision Training

10 October 2017
Paulius Micikevicius
Sharan Narang
Jonah Alben
G. Diamos
Erich Elsen
David García
Boris Ginsburg
Michael Houston
Oleksii Kuchaiev
Ganesh Venkatesh
Hao Wu
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Papers citing "Mixed Precision Training"

15 / 265 papers shown
Title
Generating Long Sequences with Sparse Transformers
Generating Long Sequences with Sparse Transformers
R. Child
Scott Gray
Alec Radford
Ilya Sutskever
11
1,844
0
23 Apr 2019
CornerNet-Lite: Efficient Keypoint Based Object Detection
CornerNet-Lite: Efficient Keypoint Based Object Detection
Hei Law
Yun Teng
Olga Russakovsky
Jia Deng
13
174
0
18 Apr 2019
SimpleDet: A Simple and Versatile Distributed Framework for Object
  Detection and Instance Recognition
SimpleDet: A Simple and Versatile Distributed Framework for Object Detection and Instance Recognition
Yuntao Chen
Chenxia Han
Yanghao Li
Zehao Huang
Yi-Xin Jiang
Naiyan Wang
Zhaoxiang Zhang
53
30
0
14 Mar 2019
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Zhaocheng Zhu
Shizhen Xu
Meng Qu
Jian Tang
GNN
11
112
0
02 Mar 2019
A Distributed Synchronous SGD Algorithm with Global Top-$k$
  Sparsification for Low Bandwidth Networks
A Distributed Synchronous SGD Algorithm with Global Top-kkk Sparsification for Low Bandwidth Networks
S. Shi
Qiang-qiang Wang
Kaiyong Zhao
Zhenheng Tang
Yuxin Wang
Xiang Huang
Xiaowen Chu
32
134
0
14 Jan 2019
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better
  Generalization
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization
Bowen Cheng
Yunchao Wei
Jiahui Yu
Shiyu Chang
Jinjun Xiong
Wen-mei W. Hwu
Thomas S. Huang
Humphrey Shi
OOD
VLM
24
6
0
23 Nov 2018
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator
Analyzing Machine Learning Workloads Using a Detailed GPU Simulator
Jonathan Lew
Deval Shah
Suchita Pati
Shaylin Cattell
Mengchi Zhang
...
Christopher Ng
Negar Goli
Matthew D. Sinclair
Timothy G. Rogers
Tor M. Aamodt
13
65
0
18 Nov 2018
Training Deep Neural Network in Limited Precision
Training Deep Neural Network in Limited Precision
Hyunsun Park
J. Lee
Youngmin Oh
Sangwon Ha
Seungwon Lee
14
8
0
12 Oct 2018
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance
  Benchmark
Analysis of DAWNBench, a Time-to-Accuracy Machine Learning Performance Benchmark
Cody Coleman
Daniel Kang
Deepak Narayanan
Luigi Nardi
Tian Zhao
Jian Zhang
Peter Bailis
K. Olukotun
Christopher Ré
Matei A. Zaharia
9
117
0
04 Jun 2018
Scaling Neural Machine Translation
Scaling Neural Machine Translation
Myle Ott
Sergey Edunov
David Grangier
Michael Auli
AIMat
14
610
0
01 Jun 2018
SNIPER: Efficient Multi-Scale Training
SNIPER: Efficient Multi-Scale Training
Bharat Singh
Mahyar Najibi
L. Davis
ObjD
22
481
0
23 May 2018
Faster Neural Network Training with Approximate Tensor Operations
Faster Neural Network Training with Approximate Tensor Operations
Menachem Adelman
Kfir Y. Levy
Ido Hakimi
M. Silberstein
18
26
0
21 May 2018
Scale out for large minibatch SGD: Residual network training on
  ImageNet-1K with improved accuracy and reduced time to train
Scale out for large minibatch SGD: Residual network training on ImageNet-1K with improved accuracy and reduced time to train
V. Codreanu
Damian Podareanu
V. Saletore
23
54
0
12 Nov 2017
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem
Deep Learning as a Mixed Convex-Combinatorial Optimization Problem
A. Friesen
Pedro M. Domingos
18
20
0
31 Oct 2017
Google's Neural Machine Translation System: Bridging the Gap between
  Human and Machine Translation
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation
Yonghui Wu
M. Schuster
Z. Chen
Quoc V. Le
Mohammad Norouzi
...
Alex Rudnick
Oriol Vinyals
G. Corrado
Macduff Hughes
J. Dean
AIMat
716
6,740
0
26 Sep 2016
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