Rustworkx Comparison Benchmarks With Other Libraries

rustworkx is competitive against other popular graph libraries for Python. We compared rustworkx to the igraph, graph-tools and NetworkIt libraries in a benchmark consisting of four tasks available on Github for reproducibility . We report the results from a machine with an Intel(R) i9-9900K CPU at 3.60GHz with eight cores, 16 theads, and 32GB of RAM avaialble.

Graph Creation

The first use benchmark consists of creating graphs with their respective nodes and edges. We compare the time to create graphs representing the USA road network from the 9th DIMACS challenge dataset (Demetrescu et al., 2009).

Single Source Shortest Path

The second benchmark is to calculate the distance two among nodes in a weighted graph. We compare the time to calculate the distance between the first and the last node in the USA road network, with the datta also coming from the 9th DIMACS challenge (Demetrescu et al., 2009). See dijkstra_shortest_path_lengths() for more information on the benchmarked function.

All-Pairs Shortest Path

The third benchmark is to calculate the distance among all nodes in a weighted graph. We compare the time to calculate the distance among all nodes in the City of Rome road network, another dataset from the 9th DIMACS challenge (Demetrescu et al., 2009). See all_pairs_dijkstra_path_lengths() for more information on the benchmarked function.

Subgraph Isomorphism

Lastly, the fourth benchamrk is about graph isomorphism. We compare the time to answer if pairs of graphs from the ARG Database are subgraph-isomorphic (De Santo et al., 2003). See is_subgraph_isomorphic() for more information on the benchmarked function.

Citation

• Demetrescu, C., Goldberg, A., & Johnson, D. The Shortest Path Problem: Ninth DIMACS Implementation Challenge.

• Santo, M. D., Foggia, P., Sansone, C., & Vento, M. (2003). A large database of graphs and its use for benchmarking graph isomorphism algorithms. Pattern Recognition Letters, 24(8), 1067–1079.