[Networkit] NetworKit 2.0 released today
christian.staudt at kit.edu
Mon Nov 11 17:14:11 CET 2013
Today we announce NetworKit 2.0, our second major release.
NetworKit is a growing open-source toolkit for high-performance network analysis. Its aim is to provide tools for the analysis of large networks in the size range from thousands to billions of edges. For this purpose, it implements efficient graph algorithms, many of them parallel to utilize multicore architectures. These are meant to quickly compute standard measures of network analysis, such as degree sequences, and clustering coefficients (see the Readme for a list of existing features and a roadmap of planned features). In this respect, NetworKit is comparable to packages like NetworkX, albeit with a focus on parallelism and scalability.
NetworKit is also a testbed for algorithm engineering and contains a few novel algorithms from recently published research, especially in the area of community detection. As of release 2.0, NetworKit is meant to be built into a Python extension module. High-performance algorithms are written in C++ and exposed to Python via Cython. Python in turn gives us the ability to work interactively and a rich environment of tools for data analysis and scientific computing.
For a download link, see the main page .
As an open-source project, we would like to encourage feedback and contributions, and thank everyone who has contributed so far. With version 2.0, we also begin a more frequent release schedule. To receive future updates and announcements, please consider subscribing to the NetworKit e-mail list .
Christian Staudt and Henning Meyerhenke
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