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Parallel Algorithms for Small Subgraph Counting [article]

Amartya Shankha Biswas, Talya Eden, Quanquan C. Liu, Slobodan Mitrović, Ronitt Rubinfeld
2020 arXiv   pre-print
In this work, we tackle this challenge and design several new algorithms for subgraph counting in the Massively Parallel Computation (MPC) model: Given a graph G over n vertices, m edges and T triangles  ...  Our second main result is an Õ_δ(loglog n)-rounds algorithm for exactly counting the number of triangles, parametrized by the arboricity α of the input graph.  ...  Counting k-cliques and 5-subgraphs. We use a similar technique for both problems of exactly counting the number of k-cliques and of subgraphs up to size 5.  ... 
arXiv:2002.08299v3 fatcat:3fkikeryq5efdflpjlta5g7hxa

Scalable Subgraph Counting: The Methods Behind The Madness

Comandur Seshadhri, Srikanta Tirthapura
2019 Companion Proceedings of The 2019 World Wide Web Conference on - WWW '19  
The basic problem is to count or approximate the occurrences of a small subgraph (the pattern) in a large graph (the dataset).  ...  We observe that there are a few common algorithmic building blocks that most subgraph counting results build on.  ...  subgraph analysis, as well as works on parallel streaming algorithms for subgraph counting.  ... 
doi:10.1145/3308560.3320092 dblp:conf/www/SeshadhriT19 fatcat:fsjcujs6krdlhmeuihzdj5h3wq

Parallel Clique Counting and Peeling Algorithms [article]

Jessica Shi and Laxman Dhulipala and Julian Shun
2021 arXiv   pre-print
We present a new parallel algorithm for k-clique counting/listing that has polylogarithmic span (parallel time) and is work-efficient (matches the work of the best sequential algorithm) for sparse graphs  ...  On a 30-core machine with two-way hyper-threading, our algorithms achieve 13.23–38.99x and 1.19–13.76x self-relative parallel speedup for k-clique counting and k-clique densest subgraph, respectively.  ...  Moreover, in both ARB-COUNT and KCLIST, node parallelism is faster on small k, while edge parallelism is faster on large k.  ... 
arXiv:2002.10047v4 fatcat:fb3vpjwfc5abffxlda5enomkty

Scalable subgraph counting using MapReduce

Ahmad Naser eddin, Pedro Ribeiro
2017 Proceedings of the Symposium on Applied Computing - SAC '17  
For that we present a dynamic iterative MapReduce strategy to parallelize algorithms that induce an unbalanced search tree, and apply it in the subgraph counting realm.  ...  The main goal of this paper is to contribute towards subgraph search, by providing an accessible and scalable parallel methodology for counting subgraphs.  ...  Using G-Tries to Count Subgraphs Algorithm 1 details how we can use g-tries to count subgraphs.  ... 
doi:10.1145/3019612.3019744 dblp:conf/sac/EddinR17 fatcat:w4cy2p6abnc57o4iuenmawvwo4

Fast Approximate Subgraph Counting and Enumeration

George M. Slota, Kamesh Madduri
2013 2013 42nd International Conference on Parallel Processing  
We present a new shared-memory parallel algorithm and implementation called FASCIA for the problems of approximate subgraph counting and subgraph enumeration.  ...  With our new counting scheme, data layout optimizations, and multicore parallelism, we demonstrate a significant speedup over the current state-of-the-art for subgraph counting.  ...  It is beneficial to parallelize across the entire count (line 3 of Algorithm 1) for smaller graphs, as memory requirements are not an issue and parallelization over a small number of vertices incurs relatively  ... 
doi:10.1109/icpp.2013.30 dblp:conf/icpp/SlotaM13 fatcat:cegq6vtsqbc3nhu3xwfsnfwwwq

Complex Network Analysis Using Parallel Approximate Motif Counting

George M. Slota, Kamesh Madduri
2014 2014 IEEE 28th International Parallel and Distributed Processing Symposium  
Determining exact subgraph counts is computationally very expensive. In recent work, we present FASCIA, a shared-memory parallel algorithm and implementation for approximate subgraph counting.  ...  We also present a simple parallelization strategy for distributed subgraph counting on smaller networks.  ...  We thank Siva Rajamanickam (Sandia Labs) for facilitating timely access to computing resources at Sandia.  ... 
doi:10.1109/ipdps.2014.50 dblp:conf/ipps/SlotaM14 fatcat:uynrdx33p5dtxktuzaypdizphq

A Survey on Subgraph Counting: Concepts, Algorithms and Applications to Network Motifs and Graphlets [article]

Pedro Ribeiro, Pedro Paredes, Miguel E.P. Silva, David Aparicio, Fernando Silva
2019 arXiv   pre-print
Counting subgraphs is however computationally very expensive and there has been a large body of work on efficient algorithms and strategies to make subgraph counting feasible for larger subgraphs and networks  ...  This survey aims precisely to provide a comprehensive overview of the existing methods for subgraph counting.  ...  Here we are interested in algorithms that count small, connected, non-isomorphic subgraphs on a single network.  ... 
arXiv:1910.13011v1 fatcat:ntfvanxbafdlfkyawb64dwxnpa

High-Performance Massive Subgraph Counting using Pipelined Adaptive-Group Communication [article]

Langshi Chen, Bo Peng, Sabra Ossen, Anil Vullikanti, Madhav Marathe, Lei Jiang, Judy Qiu
2018 arXiv   pre-print
We discuss efficient parallel algorithms for approximately resolving subgraph counting problems by using the color-coding technique.  ...  In this chapter, we study the subgraph counting problem from a parallel computing perspective.  ...  Acknowledgments We gratefully acknowledge generous support from the Intel Parallel Computing Center (IPCC) grant, NSF OCI-114932 (Career: Programming Environments and Runtime for Data Enabled Science),  ... 
arXiv:1804.09764v1 fatcat:2vqvcohjf5fsjdoj3ch5xlhjzm

A Comparative Study on Exact Triangle Counting Algorithms on the GPU

Leyuan Wang, Yangzihao Wang, Carl Yang, John D. Owens
2016 Proceedings of the ACM Workshop on High Performance Graph Processing - HPGP '16  
We implement exact triangle counting in graphs on the GPU using three different methodologies: subgraph matching to a triangle pattern; programmable graph analytics, with a set-intersection approach; and  ...  Acknowledgements Thanks to Seshadhri Comandur for providing the CPU baseline code for comparisons.  ...  Thanks also to NVIDIA for equipment donations and server time.  ... 
doi:10.1145/2915516.2915521 dblp:conf/hpdc/WangWYO16 fatcat:tqpllepszvgujet2mfgirfrfwa

Efficient Parallel Subgraph Counting Using G-Tries

Pedro Ribeiro, Fernando Silva, Luis Lopes
2010 2010 IEEE International Conference on Cluster Computing  
In this paper we present a parallel algorithm based precisely on gtries that is able to efficiently find and count subgraphs.  ...  The subgraph count is by itself a very powerful characterization of a network and it is crucial for other important network measurements.  ...  CONCLUSION In this paper we presented a novel parallel algorithm to count subgraphs.  ... 
doi:10.1109/cluster.2010.27 dblp:conf/cluster/RibeiroSL10 fatcat:zgzntzq7jbh6dam5uxpowoq5gu

Map-Reduce based Frequent Sub-Graph Extraction

Ch. Sudhakar, Assistant Professor, CSE, Vignan's Institute of Information Technology, Visakhapatnam. India, A.Siva Pavan, N. Thirupathi Rao, Debnath Bhattacharyya, III B.Tech CSE, Vignan's Institute of Information Technology, Visakhapatnam. India, Associate Professor, Vignan's Institute of Information Technology, Visakhapatnam. India, Professor, Vignan's Institute of Information Technology, Visakhapatnam. India
2020 International Journal of Multimedia and Ubiquitous Engineering  
Frequent subgraph extraction from a substantial number of small graphs is a crude activity for some, information mining applications.  ...  Parallelizing existing strategies straightforwardly utilizing MapReduce does not yield great execution as it is hard to adjust the remaining task at hand among the figure hubs.  ...  Several authors developed algorithms for parallelization of extracting subgraphs from a large number of graphs in a data set.  ... 
doi:10.21742/ijmue.2020.15.1.03 fatcat:ncalgvuhtzejdg3zq3yocrpd3u

The Glasgow Subgraph Solver: Using Constraint Programming to Tackle Hard Subgraph Isomorphism Problem Variants [chapter]

Ciaran McCreesh, Patrick Prosser, James Trimble
2020 Lecture Notes in Computer Science  
The Glasgow Subgraph Solver provides an implementation of state of the art algorithms for subgraph isomorphism problems.  ...  We outline its key features from the view of both users and algorithm developers, and discuss future directions.  ...  We would like to thank Blair Archibald, Fraser Dunlop, Jan Elffers, Stephan Gocht, Ruth Hoffmann, Jakob Nordström, and Christine Solnon for their contributions to the design and implementation of the solver  ... 
doi:10.1007/978-3-030-51372-6_19 fatcat:orm2rsy5obabnfkb34fghx7gv4

Efficient cohesive subgraphs detection in parallel

Yingxia Shao, Lei Chen, Bin Cui
2014 Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14  
In this paper, we propose a novel parallel and efficient truss detection algorithm, called PETA. The PETA produces a triangle complete subgraph (TC-subgraph) for every computing node.  ...  Based on the TC-subgraphs, PETA can detect the local k-truss in parallel within a few iterations.  ...  The algorithm constructs a triangle complete subgraph (or TC-subgraph for short), for each computing node. On basis of TC-subgraphs, the algorithm can find the local k-trusses in parallel.  ... 
doi:10.1145/2588555.2593665 dblp:conf/sigmod/ShaoCC14 fatcat:tluy5ymdenhhrm66rwhu3lk4bu

RECEIPT: REfine CoarsE-grained IndePendent Tasks for Parallel Tip decomposition of Bipartite Graphs [article]

Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna, Cesar A. F. De Rose
2020 arXiv   pre-print
Tip decomposition is a crucial kernel for mining dense subgraphs in bipartite networks, with applications in spam detection, analysis of affiliation networks etc.  ...  To build the hierarchy, existing algorithms iteratively follow a delete-update(peeling) process: deleting vertices with the minimum number of butterflies and correspondingly updating the butterfly count  ...  However, a small value of reduces parallelism in RECEIPT FD and makes the induced subgraphs larger.  ... 
arXiv:2010.08695v1 fatcat:yybhbhnmdfabvh3bqmd7b5ij7e

Parallel color-coding

George M. Slota, Kamesh Madduri
2015 Parallel Computing  
In this work, by efficiently parallelizing steps in color-coding, we create two new biological protein interaction network analysis tools: Fascia for subgraph counting and motif finding and FastPath for  ...  Subgraph counting and enumeration are compute-intensive problems.  ...  Using these optimizations, we create sharedand distributed-memory parallelized Fascia, a fast and memory-efficient tool for subgraph counting on both small and large networks.  ... 
doi:10.1016/j.parco.2015.02.004 fatcat:hbut56hljnalzmjdfzw5aof7eq
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