SNAP (Small-world Network Analysis and Partitioning) is an extensible parallel framework for exploratory analysis and partitioning of large-scale networks.
SNAP is implemented in C, uses OpenMP primitives for parallelization, and targets sequential, multicore, and symmetric multiprocessor platforms. Our intent with SNAP is to provide a simple and intuitive interface for network analysis and application design, hiding the parallel programming complexity from the user. In addition to path-based, centrality, and community identification queries on large-scale graphs, we support commonly-used preprocessing kernels and quantitative measures that help understand the global network topology.





Kamesh Madduri and David A. Bader are the primary developers of SNAP. Nicolas Bitouze (ENS Cachan) and Arvind Batra (Georgia Tech) have contributed important modules.


For related publications, please visit the home pages of Kamesh Madduri and David A. Bader.