skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Communication Quantization for Data-parallel Training of Deep Neural Networks

Authors:
; ; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1335772
Report Number(s):
LLNL-CONF-700919
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Conference
Resource Relation:
Conference: Presented at: Machine Learning in HPC Environments, Salt Lake City, UT, United States, Nov 13 - Nov 18, 2016
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

Dryden, N J, Moon, T Y, Jacobs, S A, and Van Essen, B C. Communication Quantization for Data-parallel Training of Deep Neural Networks. United States: N. p., 2016. Web.
Dryden, N J, Moon, T Y, Jacobs, S A, & Van Essen, B C. Communication Quantization for Data-parallel Training of Deep Neural Networks. United States.
Dryden, N J, Moon, T Y, Jacobs, S A, and Van Essen, B C. Tue . "Communication Quantization for Data-parallel Training of Deep Neural Networks". United States. https://www.osti.gov/servlets/purl/1335772.
@article{osti_1335772,
title = {Communication Quantization for Data-parallel Training of Deep Neural Networks},
author = {Dryden, N J and Moon, T Y and Jacobs, S A and Van Essen, B C},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2016},
month = {8}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share: