Multi-threaded modularity based graph clustering using the multilevel paradigm
We present efficient serial and parallel algorithms for modularity maximization. We show that these algorithms run in O(m+n) O ( m + n ) time and O(m+n) O ( m + n ) space. These algorithms produce clusterings of high modularity. These algorithms are 2.744 times faster than current methods. These algorithms clustered a graph with 3.3 billion edges in under 90 s.
multi-threading graph clustering multilevel paradigm shared-memory parallel