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Quantifying and Improving Performance of Distributed Deep Learning with
  Cloud Storage

Quantifying and Improving Performance of Distributed Deep Learning with Cloud Storage

13 August 2021
Nicholas Krichevsky
M. S. Louis
Tian Guo
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Papers citing "Quantifying and Improving Performance of Distributed Deep Learning with Cloud Storage"

4 / 4 papers shown
Title
Enabling All In-Edge Deep Learning: A Literature Review
Enabling All In-Edge Deep Learning: A Literature Review
Praveen Joshi
Mohammed Hasanuzzaman
Chandra Thapa
Haithem Afli
T. Scully
21
22
0
07 Apr 2022
Data science and Machine learning in the Clouds: A Perspective for the
  Future
Data science and Machine learning in the Clouds: A Perspective for the Future
H. Barua
11
5
0
02 Sep 2021
Importance of Data Loading Pipeline in Training Deep Neural Networks
Importance of Data Loading Pipeline in Training Deep Neural Networks
Mahdi Zolnouri
Xinlin Li
V. Nia
75
16
0
21 Apr 2020
Deep Learning Training in Facebook Data Centers: Design of Scale-up and
  Scale-out Systems
Deep Learning Training in Facebook Data Centers: Design of Scale-up and Scale-out Systems
Maxim Naumov
John Kim
Dheevatsa Mudigere
Srinivas Sridharan
Xiaodong Wang
...
Krishnakumar Nair
Isabel Gao
Bor-Yiing Su
Jiyan Yang
M. Smelyanskiy
GNN
41
83
0
20 Mar 2020
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