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, and NetworKit Louvain by 50x, 22x, and 20x 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.

翻译：社区检测是识别网络中自然划分的问题。在数据集规模已达到显著水平的众多应用中，高效识别此类划分的并行算法至关重要。本技术报告展示了Louvain算法（一种高质量社区检测方法）最高效的多核实现之一。在配备双路16核Intel Xeon Gold 6226R处理器的服务器上，我们提出的Louvain算法（命名为GVE-Louvain）性能分别超越Vite、Grappolo和NetworKit Louvain达50倍、22倍和20倍——在38亿条边的图上实现了5.6亿条边/秒的处理速率。此外，GVE-Louvain在线程数每翻倍时，性能平均提升1.6倍。