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Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

RESOURCE

Publicly Accessible Repository
https://github.com/bdsullivan/INDDGO
https://doi.org/10.11578/dc.20171025.1391

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Abstract

The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.
Release Date:
2012-05-30
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
2325
Site Accession Number:
4984
Research Org.:
Oak Ridge National Laboratory
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/bdsullivan/INDDGO
https://doi.org/10.11578/dc.20171025.1391

SAVE / SHARE



ORNL Badge

Citation Formats

Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO). Computer Software. https://github.com/bdsullivan/INDDGO. USDOE. 30 May. 2012. Web. doi:10.11578/dc.20171025.1391.
(2012, May 30). Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO). [Computer software]. https://github.com/bdsullivan/INDDGO. https://doi.org/10.11578/dc.20171025.1391.
"Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)." Computer software. May 30, 2012. https://github.com/bdsullivan/INDDGO. https://doi.org/10.11578/dc.20171025.1391.
@misc{ doecode_2325,
title = {Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)},
author = ,
abstractNote = {The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.},
doi = {10.11578/dc.20171025.1391},
url = {https://doi.org/10.11578/dc.20171025.1391},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20171025.1391}},
year = {2012},
month = {may}
}