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Title: Toward Training a Large 3D Cosmological CNN with Hybrid Parallelization

Authors:
 [1];  [2];  [3];  [4];  [4];  [5];  [3];  [4];  [2]
  1. Tokyo Institute of Technology
  2. Lawrence Livermore National Laboratory
  3. University of Illinois at Urbana-Champaign
  4. Lawrence Berkeley National Laboratory
  5. RIKEN
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1548314
Report Number(s):
LLNL-CONF-778764
972864
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Conference
Resource Relation:
Conference: Kitami, null, Japan
Country of Publication:
United States
Language:
English
Subject:
Computer science

Citation Formats

Oyama, Y, Maruyama, N, Dryden, N, Harrington, P, Balewski, J, Matsuoka, S, Snir, M, Nugent, P, and Van Essen, B. Toward Training a Large 3D Cosmological CNN with Hybrid Parallelization. United States: N. p., 2019. Web.
Oyama, Y, Maruyama, N, Dryden, N, Harrington, P, Balewski, J, Matsuoka, S, Snir, M, Nugent, P, & Van Essen, B. Toward Training a Large 3D Cosmological CNN with Hybrid Parallelization. United States.
Oyama, Y, Maruyama, N, Dryden, N, Harrington, P, Balewski, J, Matsuoka, S, Snir, M, Nugent, P, and Van Essen, B. Wed . "Toward Training a Large 3D Cosmological CNN with Hybrid Parallelization". United States. https://www.osti.gov/servlets/purl/1548314.
@article{osti_1548314,
title = {Toward Training a Large 3D Cosmological CNN with Hybrid Parallelization},
author = {Oyama, Y and Maruyama, N and Dryden, N and Harrington, P and Balewski, J and Matsuoka, S and Snir, M and Nugent, P and Van Essen, B},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {6}
}

Conference:
Other availability
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