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arXiv:1403.3005cs.SI

NetworKit: A Tool Suite for Large-scale Complex Network Analysis

Christian L. Staudt, Aleksejs Sazonovs, Henning Meyerhenke

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Abstract

We introduce NetworKit, an open-source software package for analyzing the structure of large complex networks. Appropriate algorithmic solutions are required to handle increasingly common large graph data sets containing up to billions of connections. We describe the methodology applied to develop scalable solutions to network analysis problems, including techniques like parallelization, heuristics for computationally expensive problems, efficient data structures, and modular software architecture. Our goal for the software is to package results of our algorithm engineering efforts and put them into the hands of domain experts. NetworKit is implemented as a hybrid combining the kernels written in C++ with a Python front end, enabling integration into the Python ecosystem of tested tools for data analysis and scientific computing. The package provides a wide range of functionality (including common and novel analytics algorithms and graph generators) and does so via a convenient interface. In an experimental comparison with related software, NetworKit shows the best performance on a range of typical analysis tasks.

arXiv comments
21 pages
Journal reference
DOI
Subjects
cs.SISocial and Information Networks cs.DCDistributed, Parallel, and Cluster Computing physics.soc-phPhysics and Society

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    • Companion paper with more details about NetworKit architecture and comparisons against Igraph and Graph-tool: https://arxiv.org/abs/1403.3005

      angrimanView on HNParent context

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