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Title: DiHydrogen

Abstract

DiHydrogen is the second version of the Hydrogen fork of the well-known distributed linear algebra library, Elemental. DiHydrogen is a GPU-accelerated distributed multilinear algebra interface with a particular emphasis on the needs of the scalable distributed deep learning training and inference. DiHydrogen is part of the Livermore Big Artificial Neural Network (LBANN) software stack.

Developers:
 [1];  [1];  [1];  [1];  [1];  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Release Date:
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Version:
0.1
Licenses:
Apache License 2.0
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)

Primary Award/Contract Number:
AC52-07NA27344
Code ID:
33387
Site Accession Number:
1003667
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Country of Origin:
United States

Citation Formats

Maruyama, Naoya, Essen, Brian Van, Dryden, Nikoli J, Benson, Thomas R, Moon, Timothy Y, Oyama, Yosuke, and USDOE National Nuclear Security Administration. DiHydrogen. Computer software. https://www.osti.gov//servlets/purl/1581178. Vers. 0.1. USDOE National Nuclear Security Administration (NNSA). 16 Dec. 2020. Web. doi:10.11578/dc.20200106.1.
Maruyama, Naoya, Essen, Brian Van, Dryden, Nikoli J, Benson, Thomas R, Moon, Timothy Y, Oyama, Yosuke, & USDOE National Nuclear Security Administration. (2020, December 16). DiHydrogen (Version 0.1) [Computer software]. https://www.osti.gov//servlets/purl/1581178. doi:10.11578/dc.20200106.1.
Maruyama, Naoya, Essen, Brian Van, Dryden, Nikoli J, Benson, Thomas R, Moon, Timothy Y, Oyama, Yosuke, and USDOE National Nuclear Security Administration. DiHydrogen. Computer software. Version 0.1. December 16, 2020. https://www.osti.gov//servlets/purl/1581178. doi:10.11578/dc.20200106.1.
@misc{osti_1581178,
title = {DiHydrogen, Version 0.1},
author = {Maruyama, Naoya and Essen, Brian Van and Dryden, Nikoli J and Benson, Thomas R and Moon, Timothy Y and Oyama, Yosuke and USDOE National Nuclear Security Administration},
abstractNote = {DiHydrogen is the second version of the Hydrogen fork of the well-known distributed linear algebra library, Elemental. DiHydrogen is a GPU-accelerated distributed multilinear algebra interface with a particular emphasis on the needs of the scalable distributed deep learning training and inference. DiHydrogen is part of the Livermore Big Artificial Neural Network (LBANN) software stack.},
url = {https://www.osti.gov//servlets/purl/1581178},
doi = {10.11578/dc.20200106.1},
year = {2020},
month = {12},
note =
}

Software:
Publicly Accessible Repository
https://github.com/llnl/dihydrogen

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