If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. Hash-table-based method requires more waiting time to synchronize and update information. An algorithm for dividing graphs into isolate sets is given, and its computation complexity is equivalent to breadth-first search. https://doi.org/10.1109/SPW.2014.22, Sattar NS (2019) Scalable community detection using distributed Louvain algorithm. #. https://doi.org/10.1145/3373464.3373473. \(\square \). arXiv preprint: arXiv:1708.00977, Chakraborty T, Dalmia A, Mukherjee A, Ganguly N (2017) Metrics for community analysis: a survey. https://doi.org/10.1088/1742-5468/2008/10/P10008, Moradi E, Fazlali M, Tabatabaee Malazi H (2015) Fast parallel community detection algorithm based on modularity. Clauset, A., Newman, M.E.J., & Moore, C. Finding community structure in very large networks. arXiv preprint, 2020. arXiv:2002.08537. The map equation. Fortunato, S. Community detection in graphs. In: 2018 IEEE 16th International Conference on Dependable, Autonomic and Secure Computing (DASC 2018), pp. In: 2018 IEEE international parallel and distributed processing symposium (IPDPS), pp 885895. 17. However, with the growth of networks sizes, the scales of graphs are consequently increasing, which means that it may be highly time-consuming for the Louvain method; therefore, many researchers have proposed parallel Louvain algorithms16,17. https://doi.org/10.1145/1772690.1772755, Li Z, Zhang S, Wang RS, Zhang XS, Chen L (2008) Quantitative function for community detection. J. Comput. 54, 2634 (2017). 16. the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Springer https://doi.org/10.1007/978-3-030-19823-7_42, Metis - serial graph partitioning and fill-reducing matrix ordering|karypis lab. https://doi.org/10.1016/j.parco.2015.03.003 (2015). Phys. The table below provides this comparison. Google Scholar, Brandes U, Delling D, Gaertler M, Grke R, Hoefer M, Nikoloski Z, Wagner D(2006) Maximizing modularity is hard. J Supercomput 78, 1027510309 (2022). 2017), information theoretic approaches (Rosvall and Bergstrom 2008), . Article Proc Natl Acad Sci 103:85778582. At the same time, the communities swap is avoided. Springer . https://doi.org/10.1007/s11390-015-1501-x (2015). SAS SUGI proceedings: customer intelligence, Pons P, Latapy M (2005) Computing communities in large networks using random walks. Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. Our method requires no extra computation and memory overhead and increases the searching spaces of the method and improves the quality of community detection. The union of these isolate sets contains the whole vertices. http://snap.stanford.edu/data, pp. In: Proceedings on the International Conference on Artificial Intelligence (ICAI), p.1. Proc. The existing PLMs traverse the vertices in order of their index. The isolate-set-based parallel Louvain method involves three stages and the pseudocodes are displayed in Algorithm 1: The first step is to partition the graph into a series of isolate sets. This is a heuristic method based on modularity optimization. Our method presents a higher speedup than hash-table-based method on 17 graph datasets. The authors implement their method on GPUs, and their work ultimately reaches the highest speedup of 270\(\times \) on several medium graphs. The computation of vertex 9 requires the information of vertex 4. That is to say, these vertices have completely different neighbors. Parallel Distrib Syst IEEE Trans 27:171184. https://doi.org/10.1038/s41598-022-11987-y, DOI: https://doi.org/10.1038/s41598-022-11987-y. MathSciNet Gopalan, P.K., & Blei, D.M. CAS 70, 118127. Phys Rev E 76(3):036106, Raghavan UN, Albert R, Kumara S (2007) Near linear time algorithm to detect community structures in large-scale networks. A 405, 8591. 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The real-time synchronization method was proposed by Que et al.15. To be specific, the first one is the latency in the synchronization of vertices information in the process of parallel computing. Que, X., Checconi, F., Petrini, F., & Gunnels, J.A. MathSciNet Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. The Lemmas 1 and 2 indicate that the maximum isolate sets can be found by the graph search algorithm. IEEE Trans Parallel Distrib Syst 1:11. Eur. https://doi.org/10.1145/3365676, Article On the datasets amazon.ungraph and web-Google, the modularity of isolate-set-based method is lower than the sequential method by 0.01%. 8491. J. Mach. Then the traversed vertices are moved once, which has the computation complexity of O(n). Every coin has two sides: the introduction of parallelization indeed accelerates Louvain but also brings implementation troubles. In: Proceedings of the 19th International Conference on World wide web, pp. https://doi.org/10.1088/1742-5468/2008/10/P10008. In order to solve the bottlenecks of synchronization latency and vertex swap in the parallelization of Louvain method, we propose a novel graph partition algorithm of isolate sets partition algorithm, which divides adjacent vertices and vertices with common adjacent vertices into a series of subgraphs. IEEE . https://doi.org/10.1007/978-3-030-23756-1_18, Traag VA (2015) Faster unfolding of communities: speeding up the Louvain algorithm. 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The final community detection performance of our method on extended graph datasets is shown in Table 3. The experimental results on popular datasets and analyses are reported as below. In: 49th International Conference on Parallel Processing-ICPP, pp. Mahmood Fazlali. The second one is that the likelihood of collision increases. https://doi.org/10.1109/BigData47090.2019.9006282, Shende SS, Malony AD (2006) The tau parallel performance system. How to bound k theoretically will be left as future work. Mar 21, 2022 -- Image taken by Ethan Unzicker from Unsplash This article will cover the fundamental intuition behind community detection and Louvain's algorithm. Naim et al.39 use two hash tables to manage the vertices information and communities information, which is different from the previous studies. Technol. & Zang, B.-Y. After the vertices swap, few mergers between the vertex happens, and the community structure remains. In the second place, we propose an algorithm to divide the graph into isolate sets, which enjoys the same computation complexity as the breadth-first search. & Li, J. Detecting overlapping communities in networks using the maximal sub-graph and the clustering coefficient. Appl Soft Comput. On the dataset LiveJournal, our method has a little lower speedup than hash-table-based method with 2 threads, because this graph has less edges (34,681,189) than others. Slider with three articles shown per slide. MathSciNet & Cui, Y. Uncovering the overlapping community structure of complex networks by maximal cliques. 47, 1937. 695701. After computing, these three vertices synchronize information to their neighbor without waiting, because the neighbor vertices are occupied by these three vertices exclusively. Flake, G.W., Lawrence, S., Giles, C.L., & Coetzee, F.M. PubMedGoogle Scholar. 529538. Experiments on 18 graphs show that our parallel method achieves a maximum 4.62 \(\times \) speedup compared with the sequential method, and outputs higher modularity on 14 graphs. The computation complexity of generating an isolate set is \(O(2n+m)\). The experiments results show that our method obtains 4.62 \(\times \) speedup on the personal computer with 8 threads and improves the modularity of communities detection in most cases. Given an undirected graph G(V,E), \(\exists {{s}_{i}}\subset G\) ( \({s}_{i}\) is isolate), \(\bigcup \nolimits _{i}^{n}{{{s}_{i}}}=G(V,E)\). https://doi.org/10.1109/JPROC.2017.2786710, Ghosh S, Halappanavar M, Tumeo A, Kalyanaraman A, Gebremedhin AH (2018) Scalable distributed memory community detection using vite. Phys Rep 486(35):75174. The proposed algorithm allocates threads to each block based on the number of required streaming multiprocessors (SMs) and warps on GPU. ACM . 227232. And vertices in the same isolate set are unable to swap communities naturally. An emerging difficulty in Web-technology-based tasks lies in dealing with graph network data, undoubtedly, which are much more complicated than traditional structured data such as lists and matrices. Google Scholar. In: Proceedings of the 22nd ACM international conference on Information & Knowledge Management, pp. https://doi.org/10.1007/978-1-4614-6729-8_6, Staudt CL, Meyerhenke H (2016) Engineering parallel algorithms for community detection in massive networks. https://doi.org/10.1109/TPDS.2015.2390633. The method has been used with success for networks of many different type (see references below) and for sizes up to 100 million nodes and billions of links. IEEE . Community structure detection has proven to be important in revealing the underlying organisation of complex networks. An algorithm for partitioning the nodes of a graph. In order to overcome the drawback, researchers have proposed several parallel Louvain methods (Parallel Louvain Method, PLM), which suffer two challenges: (1) latency in the information synchronization and (2) communities swap. Therefore, the latency in the information synchronization is reduced without computing and memory overhead. Tao, S., Dongsheng, L., & Wang, B. To further accelerate Louvain method of community detection method, we propose the definition of isolate sets in a graph, and prove several useful properties of the isolate sets. These datasets have vertices from 196,591 to 12,082,987, and edges from 899,792 to 375,535,932. During an iteration, information is updated when a subgraph has finished computing. Sci.110(36), 1453414539 (2013). Tao, S., Tianyi, C., & Dongsheng. In: 2019 IEEE International Conference on Big Data (Big Data), pp. 3241. Obviously, vertices in LiveJournal are connected stronger, which affects the efficiency of our method. Proc Natl Acad Sci 99(12):78217826. Louvain algorithm is an efficient sequential algorithm for community detection. The speedup of these methods is from 3 to 6\(\times \) based on OpenMP14 and 12\(\times \) based on GPUs33. Scientific Reports (Sci Rep) Parallel Comput 47:1937. Mach. https://doi.org/10.1109/CLUSTER.2015.11. We also thank the anonymous reviewers for the helpful comments and suggestions to improve this paper. ADS The threshold \(t_{threshold}\) is a small quantity, which improves the robustness of the algorithm and ensures that the algorithm ends properly. The Louvain+ algorithm proposed in this paper generalizes the . On this graph, the hash-table-based method has less waiting time for information synchronization, while the isolate-set-based method needs more time on the partitioning graph. The Journal of Supercomputing School of Computer, National University of Defense Technology, Changsha, 410073, China, Hang Qie,Shijie Li,Yong Dou,Jinwei Xu,Yunsheng Xiong&Zikai Gao, You can also search for this author in 49 (2014). https://doi.org/10.1016/j.parco.2015.03.003, Makris C, Pettas D, Pispirigos G (2019) Distributed community prediction for social graphs based on Louvain algorithm. https://doi.org/10.1007/s11390-015-1585-3 (2015). In: High Performance Extreme Computing Conference (HPEC), 2014 IEEE, pp. Parallel Comput 47:1937. Our method has an obviously higher speedup than the hash-table-based method. Vertices 3, 6, and 9 belong to isolate set \(s_{1}\), which are computed parallelly. Restriction vanishes on the movement of vertices in our method, which indicates that the method has more searching spaces. 631640. Learn more about Institutional subscriptions, Guendouz M, Amine A, Hamou RM (2017) discrete modified fireworks algorithm for community detection in complex networks. Physica D 238:11611167. In: 2015 IEEE International Parallel and Distributed Processing Symposium, pp. 775787 (2013). In: 2018 IEEE International Parallel and Distributed Processing Symposium (IPDPS), pp. Rosvall, M., Axelsson, D., & Bergstrom, C.T. Input: Graph G=(V,E), threshold Input: Initial community assignment, Cinit 1: Qprev . Isolate-set-based parallel Louvain method (IPLM) is proposed. Its execution time to find communities in large graphs is, therefore, a challenge. Developing distributed memory parallel algorithms is challenging because of inter-process communication and load balancing issues. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. Uses Louvain algorithm References large networks. Shen, W.Y.G.-W., Wang, W., Gong, L.-Y., Miao, Yu. Issues and bug reports are welcome at https://github.com/vtraag/louvain/issues. In: PDSW-DISCS workshop, 2019 international conference for high performance computing, networking, storage, and analysis (SC19). The algorithm divides the whole vertices of an undirected graph to several isolate sets. Sci. However, the increasing threads reduce more computation time on our method than the hash-table-based one. I. Adaptive temporal difference learning with linear function approximation. This work has been supported by Louisiana Board of Regents RCS Grant LEQSF (2017-20)-RDA-25. In: IFIP International Conference on Artificial Intelligence Applications and Innovations, pp. According to the Lemma 2, an undirected graph can be divided into several isolate sets. This is a heuristic method based on modularity optimization. The Louvain community detection algorithm is a hierarchal clustering method categorized in the NP-hard problem. After the initialization is completed, these isolate sets are traversed in turn. You are using a browser version with limited support for CSS. Acad. Functions for computing and measuring community structure. SIAM J. Algebraic Disc. Huge distinctions in the processor architecture and operation system exist between Blue Gene/Q and x86 personal computer. The limitation of our method is that partitioning isolate sets needs extra time. By submitting a comment you agree to abide by our Terms and Community Guidelines. IEEE . A 436, 665677. Provided by the Springer Nature SharedIt content-sharing initiative, Over 10 million scientific documents at your fingertips, Not logged in According to different objective functions, many kinds of community detection methods are proposed10,11,12, among which the Louvain method is a heuristic method based on modularity. Google Scholar. http://glaros.dtc.umn.edu/gkhome/metis/metis/overview, Mohammadi M, Fazlali M, Hosseinzadeh M (2021) Accelerating Louvain community detection algorithm on graphic processing unit. Article Phys Rev E 70:066111. https://doi.org/10.1103/PhysRevE.70.066111, Brandes U, Delling D, Gaertler M, Gorke R, Hoefer M, Nikoloski Z, Wagner D (2008) On modularity clustering. IEEE https://doi.org/10.1109/CADS.2015.7377794, Mosadegh MJ, Behboudi M (2011) Using social network paradigm for developing a conceptual framework in crm. In the second step, we search an isolate set \(s_i\) from the set N. Firstly, a set \(N'\) is initialized with the set N. Secondly, the two-level breadth-first search is implemented from an arbitrary vertex \(v_{j}\) in the set \(N'\). The koblenz network collection. Electron. The isolate set s is an maximum isolate set of the graph G. That is to say, there is no vertex in set \(G-s\) that can be divided to the isolate set s. Isolate set. Google Scholar. https://snap.stanford.edu/data/index.html, Staudt CL, Meyerhenke H (2016) Engineering parallel algorithms for community detection in massive networks. Phys Rev E 69:026113. https://doi.org/10.1103/PhysRevE.69.026113, Clauset A, Newman MEJ, Moore C (2004) Finding community structure in very large networks. The Louvain method is an algorithm to detect communities in large networks. & Cui, Y. Fazlali, M., Moradi, E. & Malazi, H. T. Adaptive parallel louvain community detection on a multicore platform. Bipartite-oriented distributed graph partitioning for big learning. WIREs Comput Stat e1403:113. And an arbitrary vertex \(v_{k}\) in the complementary set of G (\(v_k\in G-B_{i}\)) is in the same isolate set as the vertex \(v_{i}\). IEEE Trans. louvain-community-detection Star Here are 21 public repositories matching this topic. MATH https://doi.org/10.1016/j.neucom.2016.06.030, Newman MEJ (2006) Modularity and community structure in networks. Part of Springer Nature. Blidia, M., Chellali, M., Favaron, O., & Meddah, N. Maximal k-independent sets in graphs. A 415, 398406. Learn more about Institutional subscriptions, Arifuzzaman S, Khan M, Marathe M (2020) Fast parallel algorithms for counting and listing triangles in big graphs. The benchmark of the test is the parallel Louvain methods adapted from the parallel Louvain method based on hash tables15. The decoupling vertices can be parallelly computed without waiting for information synchronization, and the vertices cannot swap with each other in the movement. If the intersection of these two dependency sets is empty set, the subset s is called an isolate set of graph G. According to Definition 2, intersections of the dependency sets of vertices in an isolate set are empty. Correspondence to . While most current analyses focus on static networks, the detection of communities in dynamic data is both challenging and timely. Airoldi, E.M., Blei, D.M., Fienberg, S.E., & Xing, E.P. According to the density of vertices in the graph, community detection divides closely connected vertices into the same communities. A graph with high modularity has its vertices partitioned into communities, or modules, such that connections inside the communities are dense and connections to other communities are sparse. Microsyst. The parallel computing vertices are expected to be relatively independent of each other, and the relatively independent vertices reduce the latency in synchronization and thus avoid communities swap. Sci.105(4), 11181123 (2008). Efficient K-nearest-neighbor search algorithms for historical moving object trajectories. Cui, Y., Wang, X. PubMedGoogle Scholar. However, on the datesets as-skitter and com-lj.ungraph, our methods improvements are respectively 4.60% and 4.76% than the sequential method.
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