GVE-Louvain: Fast Louvain Algorithm for Community Detection in Shared Memory Setting
Abstract
Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for identifying such divisions is critical in a number of applications, where the size of datasets have reached significant scales. This technical report presents one of the most efficient multicore implementations of the Louvain algorithm, a high quality community detection method. On a server equipped with dual 16-core Intel Xeon Gold 6226R processors, our Louvain, which we term as GVE-Louvain, outperforms Vite, Grappolo, NetworKit Louvain, and cuGraph Louvain (running on NVIDIA A100 GPU) by 50x, 22x, 20x, and 5.8x faster respectively - achieving a processing rate of 560M edges/s on a 3.8B edge graph. In addition, GVE-Louvain improves performance at an average rate of 1.6x for every doubling of threads.
Keywords
Cite
@article{arxiv.2312.04876,
title = {GVE-Louvain: Fast Louvain Algorithm for Community Detection in Shared Memory Setting},
author = {Subhajit Sahu},
journal= {arXiv preprint arXiv:2312.04876},
year = {2025}
}
Comments
11 pages, 8 figures, 2 tables