Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
139 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
46 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A Survey of Distributed Graph Algorithms on Massive Graphs (2404.06037v2)

Published 9 Apr 2024 in cs.DC

Abstract: Distributed processing of large-scale graph data has many practical applications and has been widely studied. In recent years, a lot of distributed graph processing frameworks and algorithms have been proposed. While many efforts have been devoted to analyzing these, with most analyzing them based on programming models, less research focuses on understanding their challenges in distributed environments. Applying graph tasks to distributed environments is not easy, often facing numerous challenges through our analysis, including parallelism, load balancing, communication overhead, and bandwidth. In this paper, we provide an extensive overview of the current state-of-the-art in this field by outlining the challenges and solutions of distributed graph algorithms. We first conduct a systematic analysis of the inherent challenges in distributed graph processing, followed by presenting an overview of existing general solutions. Subsequently, we survey the challenges highlighted in recent distributed graph processing papers and the strategies adopted to address them. Finally, we discuss the current research trends and identify potential future opportunities.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (183)
  1. ASK-GraphView: A Large Scale Graph Visualization System. TVCG 12, 5 (2006), 669–676.
  2. Distributed Approximate Maximum Matching in the CONGEST Model. In DISC 2018 (LIPIcs, Vol. 121). 6:1–6:17.
  3. Increasing the parallelism of graph coloring via shortcutting. In PPoPP 2020. 262–275.
  4. Mehdi Alemi and Hassan Haghighi. 2019. KTMiner: Distributed k-truss detection in big graphs. Inf. Syst. 83 (2019), 195–216.
  5. Distributed Evaluation of Subgraph Queries Using Worst-Case Optimal Low-Memory Dataflows. Proc. VLDB Endow. 11, 6 (2018), 691–704.
  6. Foundations of Modern Query Languages for Graph Databases. ACM Comput. Surv. 50, 5, Article 68 (2017), 40 pages.
  7. Distributed-Memory Parallel Algorithms for Counting and Listing Triangles in Big Graphs. CoRR abs/1706.05151 (2017). arXiv:1706.05151
  8. Joe Armstrong. 2010. erlang. Commun. ACM 53, 9 (2010), 68–75.
  9. Parallel and distributed core label propagation with graph coloring. Concurr. Comput. Pract. Exp. 31, 2 (2019).
  10. Ching Avery. 2011. Giraph: Large-scale graph processing infrastructure on hadoop. Proceedings of the Hadoop Summit. Santa Clara 11, 3 (2011), 5–9.
  11. Ariful Azad and Aydin Buluç. 2015. Distributed-Memory Algorithms for Maximal Cardinality Matching Using Matrix Algebra. In CLUSTER 2015. 398–407.
  12. Mehdi Azaouzi and Lotfi Ben Romdhane. 2017. An evidential influence-based label propagation algorithm for distributed community detection in social networks. Procedia Computer Science 112 (2017), 407–416.
  13. Nitin Chandra Badam and Yogesh Simmhan. 2014. Subgraph Rank: PageRank for Subgraph-Centric Distributed Graph Processing. In COMAD 2014. 38–49.
  14. Pycompss as an instrument for translational computer science. Computing in Science & Engineering 24, 2 (2022), 79–84.
  15. Programming languages for distributed computing systems. ACM Comput. Surv. 21, 3 (1989), 261–322.
  16. Near-Optimal Approximate Shortest Paths and Transshipment in Distributed and Streaming Models. SIAM J. Comput. 50, 3 (2021), 815–856.
  17. Solutions to the st-connectivity problem using a GPU-based distributed BFS. JPDC 76 (2015), 145–153.
  18. Communication-Efficient Jaccard similarity for High-Performance Distributed Genome Comparisons. In IPDPS 2020. 1122–1132.
  19. Fast unfolding of communities in large networks. Journal of statistical mechanics: theory and experiment 2008, 10 (2008), P10008.
  20. Distributed Memory Graph Coloring Algorithms for Multiple GPUs. In IA3 2020. 54–62.
  21. Matthias Bonne and Keren Censor-Hillel. 2019. Distributed Detection of Cliques in Dynamic Networks. In ICALP 2019 (LIPIcs, Vol. 132). 132:1–132:15.
  22. Protein function prediction via graph kernels. In ISMB 2005. 47–56.
  23. A Survey on Distributed Graph Pattern Matching in Massive Graphs. ACM Comput. Surv. 54, 2 (2022), 36:1–36:35.
  24. Ulrik Brandes. 2001. A Faster Algorithm for Betweenness Centrality, In Journal of Mathematical Sociology. Journal of Mathematical Sociology 25, 163–177.
  25. Sergey Brin and Lawrence Page. 1998. The Anatomy of a Large-Scale Hypertextual Web Search Engine. Comput. Networks 30 (1998), 107–117.
  26. Graph structure in the Web. Comput. Networks 33, 1-6 (2000), 309–320.
  27. Federico Busato and Nicola Bombieri. 2015. BFS-4K: An Efficient Implementation of BFS for Kepler GPU Architectures. IEEE Trans. Parallel Distributed Syst. 26, 7 (2015), 1826–1838.
  28. Federico Busato and Nicola Bombieri. 2016. An Efficient Implementation of the Bellman-Ford Algorithm for Kepler GPU Architectures. IEEE Trans. Parallel Distributed Syst. 27, 8 (2016), 2222–2233.
  29. Scaling graph traversal to 281 trillion edges with 40 million cores. In PPoPP 2022. 234–245.
  30. Brief Announcement: An Improved Distributed Approximate Single Source Shortest Paths Algorithm. In PODC 2021. 493–496.
  31. Apache flink: Stream and batch processing in a single engine. Bull. Tech. Comm. Learn. Technol. 38, 4 (2015).
  32. Fast distributed algorithms for testing graph properties. Distributed Comput. 32, 1 (2019), 41–57.
  33. On Distributed Listing of Cliques. In PODC 2020. 474–482.
  34. Deterministic Near-Optimal Distributed Listing of Cliques. In PODC 2022. 271–280.
  35. Scalable Single Source Shortest Path Algorithms for Massively Parallel Systems. IEEE Trans. Parallel Distributed Syst. (2017), 2031–2045.
  36. Distributed approximate k-core decomposition and min-max edge orientation: Breaking the diameter barrier. J. Parallel Distributed Comput. 147 (2021), 87–99.
  37. Near-optimal Distributed Triangle Enumeration via Expander Decompositions. J. ACM 68, 3 (2021), 21:1–21:36.
  38. Distributed Triangle Detection via Expander Decomposition. In SODA 2019. 821–840.
  39. Yi-Jun Chang and Thatchaphol Saranurak. 2019. Improved Distributed Expander Decomposition and Nearly Optimal Triangle Enumeration. In PODC 2019. 66–73.
  40. Introducing OpenSHMEM: SHMEM for the PGAS community. In PGAS 2010. 1–3.
  41. X10: an object-oriented approach to non-uniform cluster computing. Acm Sigplan Notices 40, 10 (2005), 519–538.
  42. Shiri Chechik and Doron Mukhtar. 2019. Optimal Distributed Coloring Algorithms for Planar Graphs in the LOCAL model. In SODA 2019. 787–804.
  43. Shiri Chechik and Doron Mukhtar. 2022. Single-source shortest paths in the CONGEST model with improved bounds. Distributed Comput. 35, 4 (2022), 357–374.
  44. G-Miner: an efficient task-oriented graph mining system. In EuroSys 2018. 32:1–32:12.
  45. Jie Chen and Xiang Li. 2021. A Minimal Memory Game-Based Distributed Algorithm to Vertex Cover of Networks. In ISCAS 2021. 1–5.
  46. Jie Chen and Xiang Li. 2023. Toward the minimum vertex cover of complex networks using distributed potential games. Sci. China Inf. Sci. 66, 1 (2023).
  47. Jingji Chen and Xuehai Qian. 2023. Khuzdul: Efficient and Scalable Distributed Graph Pattern Mining Engine. In ASPLOS 2023. 413–426.
  48. Distributed algorithms for k-truss decomposition. In IEEE BigData 2014. 471–480.
  49. FlexMiner: A Pattern-Aware Accelerator for Graph Pattern Mining. In ISCA 2021. 581–594.
  50. Power-Law Distributions in Empirical Data. SIAM Rev. 51, 4 (2009), 661–703.
  51. Scaling Up a Distributed Computing Of Similarity Coefficient with Mapreduce. Int. J. Comput. Sci. Appl. 12, 2 (2015), 81–98.
  52. Simple and Fast Distributed Computation of Betweenness Centrality. In INFOCOM 2020. 337–346.
  53. Survey of methodologies, approaches, and challenges in parallel programming using high-performance computing systems. Scientific Programming 2020 (2020), 1–19.
  54. Leonardo Dagum and Ramesh Menon. 1998. OpenMP: an industry standard API for shared-memory programming. IEEE computational science and engineering 5, 1 (1998), 46–55.
  55. GraphH: A Processing-in-Memory Architecture for Large-Scale Graph Processing. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38, 4 (2019), 640–653.
  56. Wake up and join me! An energy-efficient algorithm for maximal matching in radio networks. Distributed Comput. 36, 3 (2023), 373–384.
  57. Jeffrey Dean and Sanjay Ghemawat. 2004. MapReduce: Simplified Data Processing on Large Clusters. In OSDI 2004. 137–150.
  58. A discussion on the design of graph database benchmarks. In Technology Conference on Performance Evaluation and Benchmarking. 25–40.
  59. Michael Elkin. 2020. Distributed Exact Shortest Paths in Sublinear Time. J. ACM 67, 3 (2020), 15:1–15:36.
  60. Distributed Maximum Matching in Bounded Degree Graphs. In Proceedings of the 2015 International Conference on Distributed Computing and Networking, ICDCN 2015. 18:1–18:10.
  61. GraphScope: A Unified Engine For Big Graph Processing. Proc. VLDB Endow. 14, 12 (2021), 2879–2892.
  62. Distributed computing connected components with linear communication cost. Distributed Parallel Databases 36, 3 (2018), 555–592.
  63. Sebastian Forster and Danupon Nanongkai. 2018. A Faster Distributed Single-Source Shortest Paths Algorithm. In FOCS 2018. 686–697.
  64. Message P Forum. 1994. MPI: A message-passing interface standard.
  65. JoCaml: A language for concurrent distributed and mobile programming. In International School on Advanced Functional Programming. 129–158.
  66. Pierre Fraigniaud and Dennis Olivetti. 2017. Distributed Detection of Cycles. In Proceedings of the 29th ACM Symposium on Parallelism in Algorithms and Architectures, SPAA 2017. 153–162.
  67. Harold N Gabow. 2017. The weighted matching approach to maximum cardinality matching. Fundamenta Informaticae 154, 1-4 (2017), 109–130.
  68. A Distributed Algorithm for Minimum-Weight Spanning Trees. ACM Trans. Program. Lang. Syst. 5, 1 (1983), 66–77.
  69. A Sublinear Time Distributed Algorithm for Minimum-Weight Spanning Trees. SIAM J. Comput. 27, 1 (1998), 302–316.
  70. Near-Optimal Distributed Maximum Flow. SIAM J. Comput. 47, 6 (2018), 2078–2117.
  71. Sayan Ghosh. 2022. Improved Distributed-memory Triangle Counting by Exploiting the Graph Structure. In HPEC 2022. 1–6.
  72. Sayan Ghosh and Mahantesh Halappanavar. 2020. TriC: Distributed-memory Triangle Counting by Exploiting the Graph Structure. In HPEC 2020. 1–6.
  73. Distributed Louvain Algorithm for Graph Community Detection. In 2018 IEEE International Parallel and Distributed Processing Symposium, IPDPS 2018. 885–895.
  74. Andrew V. Goldberg and Chris Harrelson. 2005. Computing the shortest path: A search meets graph theory. In SODA 2005. 156–165.
  75. PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs. In OSDI 2012. 17–30.
  76. GraphX: Graph Processing in a Distributed Dataflow Framework. In OSDI 2014. 599–613.
  77. William D Gropp. 2001. Learning from the Success of MPI. In Int. Conf. High-Perf. Comput. 81–92.
  78. Distributed Algorithms on Exact Personalized PageRank. In SIGMOD 2017. 479–494.
  79. Shubhankar Gupta and Suresh Sundaram. 2023. Moving-Landmark Assisted Distributed Learning Based Decentralized Cooperative Localization (DL-DCL) with Fault Tolerance. In AAAI 2023. 6175–6182.
  80. Minyang Han and Khuzaima Daudjee. 2015. Giraph Unchained: Barrierless Asynchronous Parallel Execution in Pregel-like Graph Processing Systems. Proc. VLDB Endow. 8, 9 (2015), 950–961.
  81. Yiran He and Hoi-To Wai. 2021. Provably Fast Asynchronous And Distributed Algorithms For Pagerank Centrality Computation. In ICASSP 2021. 5050–5054.
  82. Scalable graph processing frameworks: A taxonomy and open challenges. ACM Comput. Surv. 51, 3 (2018), 1–53.
  83. Scalable Graph Processing Frameworks: A Taxonomy and Open Challenges. ACM Comput. Surv. 51, 3 (2018), 60:1–60:53.
  84. A Deterministic Almost-Tight Distributed Algorithm for Approximating Single-Source Shortest Paths. SIAM J. Comput. 50, 3 (2021).
  85. DistTC: High Performance Distributed Triangle Counting. In HPEC 2019. 1–7.
  86. A round-efficient distributed betweenness centrality algorithm. In PPoPP 2019. 272–286.
  87. Stephan Holzer and Roger Wattenhofer. 2012. Optimal distributed all pairs shortest paths and applications. In PODC 2012. 355–364.
  88. Nearly Optimal Distributed Algorithm for Computing Betweenness Centrality. In 36th IEEE International Conference on Distributed Computing Systems, ICDCS 2016. 271–280.
  89. An Adaptive Parallel Algorithm for Computing Connected Components. IEEE Trans. Parallel Distributed Syst. 28, 9 (2017), 2428–2439.
  90. Parallel Algorithm for Incremental Betweenness Centrality on Large Graphs. IEEE Trans. Parallel Distributed Syst. 29, 3 (2018), 659–672.
  91. Glen Jeh and Jennifer Widom. 2002. SimRank: a measure of structural-context similarity. In KDD 2002. 538–543.
  92. Yichuan Jiang. 2016. A Survey of Task Allocation and Load Balancing in Distributed Systems. IEEE Trans. Parallel Distributed Syst. 27, 2 (2016), 585–599.
  93. High-Level Programming Abstractions for Distributed Graph Processing. IEEE Trans. Knowl. Data Eng. 30, 2 (2018), 305–324.
  94. George Karypis and Vipin Kumar. 1997. METIS: A software package for partitioning unstructured graphs, partitioning meshes, and computing fill-reducing orderings of sparse matrices. (1997).
  95. Harold W Kuhn. 1955. The Hungarian method for the assignment problem. Nav. Res. Logist. Q. 2, 1-2 (1955), 83–97.
  96. Scalable Subgraph Enumeration in MapReduce. 8, 10 (2015), 974–985.
  97. Distributed Subgraph Matching on Timely Dataflow. Proc. VLDB Endow. 12, 10 (2019), 1099–1112.
  98. GLogS: Interactive Graph Pattern Matching Query At Large Scale. In USENIX ATC 23. 53–69.
  99. Accelerating PageRank using Partition-Centric Processing. In USENIX ATC 2018. 427–440.
  100. Sebastian Lamm and Peter Sanders. 2022. Communication-efficient Massively Distributed Connected Components. In IPDPS 2022. 302–312.
  101. Distributed Distance Computation and Routing with Small Messages. Distrib. Comput. 32, 2 (2019), 133–157.
  102. Walking in the Cloud: Parallel SimRank at Scale. Proc. VLDB Endow. 9, 1 (2015), 24–35.
  103. Distributed D-core Decomposition over Large Directed Graphs. Proc. VLDB Endow. 15, 8 (2022), 1546–1558.
  104. Wenqing Lin. 2019. Distributed Algorithms for Fully Personalized PageRank on Large Graphs. In WWW 2019. 1084–1094.
  105. Distributed (α𝛼\alphaitalic_α, β𝛽\betaitalic_β)-Core Decomposition over Bipartite Graphs. In ICDE 2023. 909–921.
  106. Distributed Direction-Optimizing Label Propagation for Community Detection. In HPEC 2019. 1–6.
  107. Distributed GraphLab: A Framework for Machine Learning in the Cloud. Proc. VLDB Endow. 5, 8 (2012), 716–727.
  108. Fast Connected Components Computation in Large Graphs by Vertex Pruning. IEEE Trans. Parallel Distributed Syst. 28, 3 (2017), 760–773.
  109. Siqiang Luo. 2019. Distributed PageRank Computation: An Improved Theoretical Study. In AAAI 2019. 4496–4503.
  110. Siqiang Luo. 2020. Improved Communication Cost in Distributed PageRank Computation - A Theoretical Study. In ICML 2020 (Proceedings of Machine Learning Research, Vol. 119). 6459–6467.
  111. Distributed PageRank computation with improved round complexities. Inf. Sci. 607 (2022), 109–125.
  112. Siqiang Luo and Zulun Zhu. 2023. Massively Parallel Single-Source SimRanks in o(log n) Rounds. CoRR abs/2304.04015 (2023). arXiv:2304.04015
  113. UniWalk: Unidirectional Random Walk Based Scalable SimRank Computation over Large Graph. In ICDE 2017. 325–336.
  114. PSPLPA: Probability and similarity based parallel label propagation algorithm on spark. Physica A: Statistical Mechanics and its Applications 503 (2018), 366–378.
  115. DSMR: a shared and distributed memory algorithm for single-source shortest path problem. In PPoPP 2016. 39:1–39:2.
  116. Pregel: a system for large-scale graph processing. In SIGMOD 2010. 135–146.
  117. The core decomposition of networks: theory, algorithms and applications. VLDB J. 29, 1 (2020), 61–92.
  118. Aritra Mandal and Mohammad Al Hasan. 2017. A distributed k-core decomposition algorithm on spark. In IEEE BigData 2017. 976–981.
  119. Ali Mashreghi and Valerie King. 2021. Broadcast and minimum spanning tree with o(m) messages in the asynchronous CONGEST model. Distributed Comput. 34, 4 (2021), 283–299.
  120. ADOPT: Asynchronous distributed constraint optimization with quality guarantees. Artificial Intelligence 161, 1-2 (2005), 149–180.
  121. Distributed k-Core Decomposition. IEEE Trans. Parallel Distributed Syst. 24, 2 (2013), 288–300.
  122. Ray: A distributed framework for emerging AI applications. In OSDI 2018. 561–577.
  123. Worst-Case Optimal Join Algorithms. J. ACM 65, 3, Article 16 (2018).
  124. Oracle. 2014. Remote Method Invocation Home. https://www.oracle.com/java/technologies/javase/remote-method-invocation-home.html
  125. Trust: Triangle Counting Reloaded on GPUs. IEEE Trans. Parallel Distributed Syst. 32, 11 (2021), 2646–2660.
  126. A time- and message-optimal distributed algorithm for minimum spanning trees. In STOC 2017. 743–756.
  127. PTE: Enumerating Trillion Triangles On Distributed Systems. In KDD 2016. 1115–1124.
  128. Faster parallel traversal of scale free graphs at extreme scale with vertex delegates. In SC 2014. IEEE, 549–559.
  129. VColor: A practical vertex-cut based approach for coloring large graphs. In ICDE 2016. 97–108.
  130. Yossi Peretz and Yigal Fischler. 2022. A fast parallel max-flow algorithm. J. Parallel Distr. Com. 169 (2022), 226–241.
  131. Near linear time algorithm to detect community structures in large-scale networks. Physical review E 76, 3 (2007), 036106.
  132. A Scalable Distributed Dynamical Systems Approach to Learn the Strongly Connected Components and Diameter of Networks. IEEE Trans. Autom. Control. 68, 5 (2023), 3099–3106.
  133. Exploiting social network graph characteristics for efficient BFS on heterogeneous chips. J. Parallel Distributed Comput. 120 (2018), 282–294.
  134. X-Stream: edge-centric graph processing using streaming partitions. In SOSP 2013. 472–488.
  135. Undirected (1+ϵitalic-ϵ\epsilonitalic_ϵ)-shortest paths via minor-aggregates: near-optimal deterministic parallel and distributed algorithms. In STOC 2022. 478–487.
  136. The family of mapreduce and large-scale data processing systems. ACM Comput. Surv. 46, 1 (2013), 11:1–11:44.
  137. Semih Salihoglu and Jennifer Widom. 2013. GPS: a graph processing system. In SSDBM 2013. 22:1–22:12.
  138. Peter Sanders and Tim Niklas Uhl. 2023. Engineering a Distributed-Memory Triangle Counting Algorithm. In IPDPS 2023. 702–712.
  139. STREAMER: A distributed framework for incremental closeness centrality computation. In CLUSTER 2013. 1–8.
  140. Fast distributed PageRank computation. Theor. Comput. Sci. 561 (2015), 113–121.
  141. Naw Safrin Sattar and Shaikh Arifuzzaman. 2018. Parallelizing Louvain Algorithm: Distributed Memory Challenges. In DASC/PiCom/DataCom/CyberSciTech 2018. 695–701.
  142. Naw Safrin Sattar and Shaikh Arifuzzaman. 2022. Scalable distributed Louvain algorithm for community detection in large graphs. J. Supercomput. 78, 7 (2022), 10275–10309.
  143. Saeed Shahrivari and Saeed Jalili. 2021. Efficient Distributed k-Clique Mining for Large Networks Using MapReduce. IEEE Trans. Knowl. Data Eng. 33, 3 (2021), 964–974.
  144. Efficient cohesive subgraphs detection in parallel. In SIGMOD 2014. 613–624.
  145. When hashes met wedges: A distributed algorithm for finding high similarity vectors. In WWW 2017. 431–440.
  146. A review on distributed application processing frameworks in smart mobile devices for mobile cloud computing. IEEE Communications surveys & tutorials 15, 3 (2012), 1294–1313.
  147. GoFFish: A Sub-graph Centric Framework for Large-Scale Graph Analytics. In Euro-Par 2014 (Lecture Notes in Computer Science, Vol. 8632). 451–462.
  148. Asynchronous distributed learning of topic models. Advances in Neural Information Processing Systems 21 (2008).
  149. PPR-partitioning: a distributed graph partitioning algorithm based on the personalized PageRank vectors in vertex-centric systems. Knowl. Inf. Syst. 61, 2 (2019), 847–871.
  150. TriPoll: computing surveys of triangles in massive-scale temporal graphs with metadata. In SC 2021. 67.
  151. Asynchronous Distributed-Memory Triangle Counting and LCC with RMA Caching. In IPDPS 2022. 291–301.
  152. Better Approximation for Distributed Weighted Vertex Cover via Game-Theoretic Learning. IEEE Trans. Syst. Man Cybern. Syst. 52, 8 (2022), 5308–5319.
  153. Distributed Optimization for Weighted Vertex Cover via Heuristic Game Theoretic Learning. In CDC 2020. 325–330.
  154. Mining maximal cliques from a large graph using mapreduce: Tackling highly uneven subproblem sizes. Journal of Parallel and distributed computing 79 (2015), 104–114.
  155. Nilothpal Talukder and Mohammed J. Zaki. 2016. A distributed approach for graph mining in massive networks. Data Min. Knowl. Discov. 30, 5 (2016), 1024–1052.
  156. Arabesque: a system for distributed graph mining. In SOSP 2015. 425–440.
  157. CORPORATE The MPI Forum. 1993. MPI: a message passing interface. In Proceedings of SC. 878–883.
  158. From ”Think Like a Vertex” to ”Think Like a Graph”. Proc. VLDB Endow. 7, 3 (2013), 193–204.
  159. The Worst-Case Time Complexity for Generating All Maximal Cliques. In COCOON 2004 (Lecture Notes in Computer Science, Vol. 3106). 161–170.
  160. Storm@ twitter. In Proceedings of SIGMOD. 147–156.
  161. Parallel and distributed Haskells. Journal of Functional Programming 12, 4-5 (2002), 469–510.
  162. Scaling Graph 500 SSSP to 140 Trillion Edges with over 40 Million Cores. In SC 2022. 19:1–19:15.
  163. DISK: A Distributed Framework for Single-Source SimRank with Accuracy Guarantee. Proc. VLDB Endow. 14, 3 (2020), 351–363.
  164. BENU: Distributed Subgraph Enumeration with Backtracking-Based Framework. In ICDE 2019. 136–147.
  165. Klaus Wehmuth and Artur Ziviani. 2013. DACCER: Distributed Assessment of the Closeness CEntrality Ranking in complex networks. Comput. Networks 57, 13 (2013), 2536–2548.
  166. Efficient Distributed Approaches to Core Maintenance on Large Dynamic Graphs. IEEE Trans. Parallel Distributed Syst. 33, 1 (2022), 129–143.
  167. Tom White. 2012. Hadoop: The definitive guide. ” O’Reilly Media, Inc.”.
  168. cuTS: scaling subgraph isomorphism on distributed multi-GPU systems using trie based data structure. In SC 2021. 69.
  169. Distributed Maximal Clique Computation and Management. IEEE Trans. Serv. Comput. 9, 1 (2016), 110–122.
  170. Distributed Maximal Clique Computation. In IEEE BigData 2014. 160–167.
  171. Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs. Proc. VLDB Endow. 7, 14 (2014), 1981–1992.
  172. Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation. In WWW 2015. 1307–1317.
  173. HUGE: An Efficient and Scalable Subgraph Enumeration System. In SIGMOD 2021. 2049–2062.
  174. A Block-Based Triangle Counting Algorithm on Heterogeneous Environments. IEEE Trans. Parallel Distributed Syst. 33, 2 (2022), 444–458.
  175. Distributed Processing of k Shortest Path Queries over Dynamic Road Networks. In SIGMOD 2020. 665–679.
  176. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. In NSDI 2012. 15–28.
  177. Spark: Cluster Computing with Working Sets. In HotCloud 2010.
  178. Apache spark: a unified engine for big data processing. Commun. ACM 59, 11 (2016), 56–65.
  179. Jianping Zeng and Hongfeng Yu. 2018. A Scalable Distributed Louvain Algorithm for Large-Scale Graph Community Detection. In CLUSTER 2018. 268–278.
  180. Distributed shortest path query processing on dynamic road networks. VLDB J. 26, 3 (2017), 399–419.
  181. A Fault-Tolerant Distributed Framework for Asynchronous Iterative Computations. IEEE Trans. Parallel Distributed Syst. 32, 8 (2021), 2062–2073.
  182. WolfGraph: The edge-centric graph processing on GPU. Future Gener. Comput. Syst. 111 (2020), 552–569.
  183. Universally-Optimal Distributed Shortest Paths and Transshipment via Graph-Based 𝓁𝓁\mathscr{l}script_l11{}_{\mbox{1}}start_FLOATSUBSCRIPT 1 end_FLOATSUBSCRIPT-Oblivious Routing. In SODA 2022. 2549–2579.
Citations (8)
View on Semantic Scholar

Summary

We haven't generated a summary for this paper yet.

Ai Sparkles Streamline Icon: https://streamlinehq.com Summarize Now
X Twitter Logo Streamline Icon: https://streamlinehq.com

Tweets