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Title: Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations

Abstract

Lawrence Livermore National Laboratory (LLNL) is a national lab based in Livermore, California. It was established in 1952 to meet increasing national security needs. They specialize in earth and atmospheric science, bioscience and bioengineering, lasers and optical science and technology, advanced materials and manufacturing, high-energy-density science, nuclear, chemical, and isotopic science and technology, and HPC, simulation and data science ((cor, 2018)). LLNL is also home to a number of large Linux clusters and supercomputers which are used to support research in their areas of specialization (mac, 2018). One purpose of the LLNL supercomputers is to run highly detailed and accurate physics simulations. These simulations allow scientists to get data on experiments that would be too expensive, difficult, or dangerous to perform in reality. With the help of simulations scientists at LLNL are able to study processes in more depth than they would be able to otherwise.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Harvey Mudd College, Claremont, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1460078
Report Number(s):
LLNL-SR-753893
939771
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Huang, Amy, Barnes, Katelyn, Bearer, Joseph, Chrisinger, Evan, and Stone, Christopher. Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations. United States: N. p., 2018. Web. doi:10.2172/1460078.
Huang, Amy, Barnes, Katelyn, Bearer, Joseph, Chrisinger, Evan, & Stone, Christopher. Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations. United States. doi:10.2172/1460078.
Huang, Amy, Barnes, Katelyn, Bearer, Joseph, Chrisinger, Evan, and Stone, Christopher. Thu . "Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations". United States. doi:10.2172/1460078. https://www.osti.gov/servlets/purl/1460078.
@article{osti_1460078,
title = {Integrating Distributed-Memory Machine Learning into Large-Scale HPC Simulations},
author = {Huang, Amy and Barnes, Katelyn and Bearer, Joseph and Chrisinger, Evan and Stone, Christopher},
abstractNote = {Lawrence Livermore National Laboratory (LLNL) is a national lab based in Livermore, California. It was established in 1952 to meet increasing national security needs. They specialize in earth and atmospheric science, bioscience and bioengineering, lasers and optical science and technology, advanced materials and manufacturing, high-energy-density science, nuclear, chemical, and isotopic science and technology, and HPC, simulation and data science ((cor, 2018)). LLNL is also home to a number of large Linux clusters and supercomputers which are used to support research in their areas of specialization (mac, 2018). One purpose of the LLNL supercomputers is to run highly detailed and accurate physics simulations. These simulations allow scientists to get data on experiments that would be too expensive, difficult, or dangerous to perform in reality. With the help of simulations scientists at LLNL are able to study processes in more depth than they would be able to otherwise.},
doi = {10.2172/1460078},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {5}
}