Grappolo

Software · Wed Feb 12 00:00:00 EST 2014

DOI:https://doi.org/10.11578/dc.20210416.46· OSTI ID:1231726 · Code ID:54751

Halappanavar, Mahantesh ^[1]

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1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed by Blondel et al. in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains (e.g., internet, citation, biological). Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number of iterations, while providing real speedups of up to 8x using 32 threads. In addition, our parallel implementation was able to exhibit weak scaling properties on up to 32 threads.

• Short Name / Acronym: GRAPPOLO
• Project Type: Open Source, Publicly Available Repository
• Site Accession Number: 5098
• Software Type: Scientific
• License(s): BSD 3-clause "New" or "Revised" License
• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE

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  Primary Award/Contract Number:

  AC06-76RL01830
• DOE Contract Number: AC06-76RL01830
• Code ID: 54751
• OSTI ID: 1231726
• Country of Origin: United States