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Title: Livermore Big Artificial Neural Network Toolkit

Abstract

LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.

Authors:
 [1];  [1];  [1];  [1];  [1]
  1. Lawrence Livermore National Laboroatory
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
Contributing Org.:
Lawrence Livermore National Laboratory
OSTI Identifier:
1271009
Report Number(s):
LBANN V.0.9; 004857MLTPL00
LLNL-CODE-697807
DOE Contract Number:  
AC52-07NA27344
Resource Type:
Software
Software Revision:
00
Software Package Number:
004857
Software CPU:
MLTPL
Open Source:
Yes
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

Essen, Brian Van, Jacobs, Sam, Kim, Hyojin, Dryden, Nikoli, and Moon, Tim. Livermore Big Artificial Neural Network Toolkit. Computer software. https://www.osti.gov//servlets/purl/1271009. Vers. 00. USDOE Office of Science (SC). 1 Jul. 2016. Web.
Essen, Brian Van, Jacobs, Sam, Kim, Hyojin, Dryden, Nikoli, & Moon, Tim. (2016, July 1). Livermore Big Artificial Neural Network Toolkit (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1271009.
Essen, Brian Van, Jacobs, Sam, Kim, Hyojin, Dryden, Nikoli, and Moon, Tim. Livermore Big Artificial Neural Network Toolkit. Computer software. Version 00. July 1, 2016. https://www.osti.gov//servlets/purl/1271009.
@misc{osti_1271009,
title = {Livermore Big Artificial Neural Network Toolkit, Version 00},
author = {Essen, Brian Van and Jacobs, Sam and Kim, Hyojin and Dryden, Nikoli and Moon, Tim},
abstractNote = {LBANN is a toolkit that is designed to train artificial neural networks efficiently on high performance computing architectures. It is optimized to take advantages of key High Performance Computing features to accelerate neural network training. Specifically it is optimized for low-latency, high bandwidth interconnects, node-local NVRAM, node-local GPU accelerators, and high bandwidth parallel file systems. It is built on top of the open source Elemental distributed-memory dense and spars-direct linear algebra and optimization library that is released under the BSD license. The algorithms contained within LBANN are drawn from the academic literature and implemented to work within a distributed-memory framework.},
url = {https://www.osti.gov//servlets/purl/1271009},
doi = {},
year = {2016},
month = {7},
note =
}