pnnl/NWHypergraph

RESOURCE

Abstract

NWHypergraph is a C++ hypergraph processing framework for shared-memory architecture. NWHypergraph provides efficient algorithms to construct s-line graphs, a lower-order approximation of a given hypergraph, and computes different graph metrics of a s-line graph such as s-connected components, s-betweenness centrality, s-closeness centrality, etc. It also provides Python APIs for s-line graph computation. The Python APIs are provided using Pybind11
Developers:
Lumsdaine, Andrew [1] Firoz, Jesun [1] Praggastis, Brenda [1] Liu, Xu [2]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. University of Washington
Release Date:
2022-06-01
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
74600
Site Accession Number:
Battelle IPID 32416-E
Research Org.:
Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
Country of Origin:
United States

RESOURCE

Citation Formats

Lumsdaine, Andrew, Firoz, Jesun, Praggastis, Brenda, and Liu, Xu. pnnl/NWHypergraph. Computer Software. https://github.com/pnnl/NWHypergraph. USDOE. 01 Jun. 2022. Web. doi:10.11578/dc.20240614.222.
Lumsdaine, Andrew, Firoz, Jesun, Praggastis, Brenda, & Liu, Xu. (2022, June 01). pnnl/NWHypergraph. [Computer software]. https://github.com/pnnl/NWHypergraph. https://doi.org/10.11578/dc.20240614.222.
Lumsdaine, Andrew, Firoz, Jesun, Praggastis, Brenda, and Liu, Xu. "pnnl/NWHypergraph." Computer software. June 01, 2022. https://github.com/pnnl/NWHypergraph. https://doi.org/10.11578/dc.20240614.222.
@misc{ doecode_74600,
title = {pnnl/NWHypergraph},
author = {Lumsdaine, Andrew and Firoz, Jesun and Praggastis, Brenda and Liu, Xu},
abstractNote = {NWHypergraph is a C++ hypergraph processing framework for shared-memory architecture. NWHypergraph provides efficient algorithms to construct s-line graphs, a lower-order approximation of a given hypergraph, and computes different graph metrics of a s-line graph such as s-connected components, s-betweenness centrality, s-closeness centrality, etc. It also provides Python APIs for s-line graph computation. The Python APIs are provided using Pybind11},
doi = {10.11578/dc.20240614.222},
url = {https://doi.org/10.11578/dc.20240614.222},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20240614.222}},
year = {2022},
month = {jun}
}