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A meta-graph approach to analyze subgraph-centric distributed programming models

Ravikant Dindokar, Neel Choudhury, Yogesh Simmhan
2016 2016 IEEE International Conference on Big Data (Big Data)  

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2015 pre-print arXiv:1508.04265v1 fatcat:vikzrhc7rvb2tauawxuc7e2fsa

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2016 accepted
arXiv:1508.04265v2 fatcat:ggpjszuvrjaplptjhbcbhfna5q
Here, we propose a analytical approach based on a meta-graph sketch to examine the characteristics of component-centric graph programming models at a coarse granularity.  ...  Component-centric distributed graph processing platforms that use a bulk synchronous parallel (BSP) programming model have gained traction.  ...  Vertex-/Subgraph-centric programming models exploit degrees of parallelism proportional to the number of vertices/subgraphs in the graph/meta-graph, respectively, within each superstep.  ... 
doi:10.1109/bigdata.2016.7840587 dblp:conf/bigdataconf/DindokarCS16 fatcat:ala4ecbsxjcfjhf3mnycw3osea
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Ravikant Dindokar, Neel Choudhury, Yogesh Simmhan. "A meta-graph approach to analyze subgraph-centric distributed programming models." 2016 IEEE International Conference on Big Data (Big Data) (2016) 37-47

Elastic Partition Placement for Non-stationary Graph Algorithms

Ravikant Dindokar, Yogesh Simmhan
2016 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)  

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2015 pre-print arXiv:1510.03145v1 fatcat:byty7z6w5jbjxb7pbwb3f25owu
Distributed graph platforms like Pregel have used vertex- centric programming models to process the growing corpus of graph datasets using commodity clusters.  ...  We validate our strategies for several graphs, using runtime tra- ces for their distributed execution of a Breadth First Search (BFS) algorithms on our subgraph-centric GoFFish graph platform.  ...  GoFFish Subgraph-centric Model As described before, GoFFish [20] is a distributed graph processing framework that follows a BSP model to ex- ecute graph application written using a subgraph-centric programming  ... 
doi:10.1109/ccgrid.2016.97 dblp:conf/ccgrid/DindokarS16 fatcat:epzmc3nxyzbunhqqzjrtl7qbka
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Ravikant Dindokar, Yogesh Simmhan. "Elastic Partition Placement for Non-stationary Graph Algorithms." 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid) (2016) 90-93

GoFFish: A Sub-graph Centric Framework for Large-Scale Graph Analytics [chapter]

Yogesh Simmhan, Alok Kumbhare, Charith Wickramaarachchi, Soonil Nagarkar, Santosh Ravi, Cauligi Raghavendra, Viktor Prasanna
2014 Lecture Notes in Computer Science  

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2013 pre-print
arXiv:1311.5949v1 fatcat:dkrxhdfnwng5jpxyp4t3k66egi
We introduce a sub-graph centric programming abstraction that combines the scalability of a vertex centric approach with the flexibility of shared memory sub-graph computation.  ...  Vertex centric programming models like Pregel are gaining traction due to their simple abstraction that allows for scalable execution on distributed systems naturally.  ...  Subgraph centric algorithms are vulnerable to imbalances in number of sub-graphs per partition and non-uniformity in their sizes. This causes stragglers.  ... 
doi:10.1007/978-3-319-09873-9_38 fatcat:5yhseslvtjavtonztczswyvdte
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Yogesh Simmhan, Alok Kumbhare, Charith Wickramaarachchi, Soonil Nagarkar, Santosh Ravi, Cauligi Raghavendra, Viktor Prasanna. "GoFFish: A Sub-graph Centric Framework for Large-Scale Graph Analytics." Lecture Notes in Computer Science (2014) 451-462

Big Graph Mining: Frameworks and Techniques

Sabeur Aridhi, Engelbert Mephu Nguifo
2016 Big Data Research  

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2016 pre-print arXiv:1602.03072v1 fatcat:avuumkds5zgn7fdq6yv6bpef7q
It also gives a categorization of both distributed data mining and machine learning techniques, graph processing frameworks and large scale pattern mining approaches.  ...  Big graph mining is an important research area and it has attracted considerable attention. It allows to process, analyze, and extract meaningful information from large amounts of graph data.  ...  Framework Asynchronous execution Resources Programming model PEGASUS No Distributed system Matrix operations Pregel No Distributed system Vertex-centric Blogel No Distributed system Graph-centric  ... 
doi:10.1016/j.bdr.2016.07.002 fatcat:sctq3qlbmndd3islrbugcxxzv4
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Sabeur Aridhi, Engelbert Mephu Nguifo. "Big Graph Mining: Frameworks and Techniques." Big Data Research (2016) 1-10

BLADYG: A Graph Processing Framework for Large Dynamic Graphs

Sabeur Aridhi, Alberto Montresor, Yannis Velegrakis
2017 Big Data Research  

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2017 pre-print
arXiv:1701.00546v1 fatcat:2f6i6w66gjacvj7gnqhol7l4uy
In block-centric approaches, the unit of computation is a block, a connected subgraph of the graph, and message exchanges occur among blocks.  ...  In vertex-centric approaches, each vertex corresponds to a process, and message are exchanged among vertices.  ...  Vertex-centric approaches divide input graphs into partitions, and employ a "think like a vertex" programming model to support iterative graph computation [16, 25] .  ... 
doi:10.1016/j.bdr.2017.05.003 fatcat:b5yc2uy7trainf5ccxe2hdxhci
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Sabeur Aridhi, Alberto Montresor, Yannis Velegrakis. "BLADYG: A Graph Processing Framework for Large Dynamic Graphs." Big Data Research (2017) 9-17

A Partition-centric Distributed Algorithm for Identifying Euler Circuits in Large Graphs [article]

Siddharth D Jaiswal, Yogesh Simmhan
2019 arXiv   pre-print

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We propose a novel partition-centric algorithm to find the Euler circuit, over large graphs partitioned across distributed machines and executed iteratively using a Bulk Synchronous Parallel (BSP) model  ...  With such cycles finding use in neuroscience and Internet of Things for large graphs, designing a distributed algorithm for finding the Euler circuit is important.  ...  Acknowledgement This work was supported by a Microsoft Data Science Fellowship provided to the first author, and a Microsoft Azure research grant for access to cloud resources.  ... 
arXiv:1903.06950v1 fatcat:tdb3wofz2jcl7o7as2plcvqj4m
Citation

Siddharth D Jaiswal, Yogesh Simmhan. "A Partition-centric Distributed Algorithm for Identifying Euler Circuits in Large Graphs." arXiv (2019)

Efficient snapshot retrieval over historical graph data

U. Khurana, A. Deshpande
2013 2013 IEEE 29th International Conference on Data Engineering (ICDE)  

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It consists of two key components: (1) a Temporal Graph Index (TGI), that compactly stores large volumes of historical graph evolution data in a partitioned and distributed fashion -TGI also provides support  ...  In this paper, we present a system, called Historical Graph Store, that enables users to store large volumes of historical graph data and to express and run complex temporal graph analytical tasks against  ...  Our approach to temporal processing in this paper is best described using a node-centric logical model, i.e., the historical graph is seen as a collection of evolving vertices over time; the edges are  ... 
doi:10.1109/icde.2013.6544892 dblp:conf/icde/KhuranaD13 fatcat:7zgoe2txena55lxfgm56ro2w3y
Citation

U. Khurana, A. Deshpande. "Efficient snapshot retrieval over historical graph data." 2013 IEEE 29th International Conference on Data Engineering (ICDE) (2013) 997-1008

Towards Balance-Affinity Tradeoff in Concurrent Subgraph Traversals

Yinglong Xia, Lifeng Nai, Jui-Hsin Lai
2015 2015 IEEE International Parallel and Distributed Processing Symposium  

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A dynamic weighted bipartite graph is built to model the affinity between subgraph traversals and processors, and the workload of processors.  ...  In this paper, we present an auction based approach for allocating concurrent subgraph traversals onto the processors.  ...  Among various solutions to linear programming, the auction based approach usually offers the richest parallelism.  ... 
doi:10.1109/ipdps.2015.25 dblp:conf/ipps/XiaNL15 fatcat:ng62xgbuzfg6fode5jnzj5hzti
Citation

Yinglong Xia, Lifeng Nai, Jui-Hsin Lai. "Towards Balance-Affinity Tradeoff in Concurrent Subgraph Traversals." 2015 IEEE International Parallel and Distributed Processing Symposium (2015) 936-945

Storing and Analyzing Historical Graph Data at Scale [article]

Udayan Khurana, Amol Deshpande
2015 arXiv   pre-print

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It consists of two key components: a Temporal Graph Index (TGI), that compactly stores large volumes of historical graph evolution data in a partitioned and distributed fashion; it provides support for  ...  In this paper, we present a system, called Historical Graph Store, that enables users to store large volumes of historical graph data and to express and run complex temporal graph analytical tasks against  ...  Our approach to temporal processing in this paper is best described using a node-centric logical model, i.e., the historical graph is seen as a collection of evolving vertices over time; the edges are  ... 
arXiv:1509.08960v1 fatcat:nagvtvgi3fdq7oelhxu3xu6uha
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Udayan Khurana, Amol Deshpande. "Storing and Analyzing Historical Graph Data at Scale." arXiv (2015)

Link mining

Lise Getoor, Christopher P. Diehl
2005 SIGKDD Explorations  

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Link mining refers to data mining techniques that explicitly consider these links when building predictive or descriptive models of the linked data.  ...  Commonly addressed link mining tasks include object ranking, group detection, collective classification, link prediction and subgraph discovery.  ...  Acknowledgments Thanks to the students in the LINQs group at UMD, especially Indrajit Bhattacharya, Mustafa Bilgic, and Prithviraj Sen for their input.  ... 
doi:10.1145/1117454.1117456 fatcat:z33bv3nf3rac5o3t43poebum7i
Citation

Lise Getoor, Christopher P. Diehl. "Link mining." SIGKDD Explorations 7.2 (2005) 3-12

ICDE conference 2015 detailed author index

2015 2015 IEEE 31st International Conference on Data Engineering  

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Event Logs: A Graph Repair Approach P continues on next page… [Search] A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Pei, Xubin 1340 DualTable: A Hybrid Storage Model for Update Optimization  ...  Sequences Song, Shaoxu 30 Cleaning Structured Event Logs: A Graph Repair Approach Soto, Juan 1191 Efficient Sample Generation for Scalable Meta Learning Soylemez, Ekrem 1253 Oracle Database In-Memory:  ... 
doi:10.1109/icde.2015.7113260 fatcat:ep7pomkm55f45j33tkpoc5asim
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"ICDE conference 2015 detailed author index." 2015 IEEE 31st International Conference on Data Engineering (2015)

Parallel subgraph listing in a large-scale graph

Yingxia Shao, Bin Cui, Lei Chen, Lin Ma, Junjie Yao, Ning Xu
2014 Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14  

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However, the centralized solutions cannot scale well to large graphs. Recently, several parallel approaches are introduced to handle the large graphs.  ...  To further reduce the enormous intermediate results, we introduce three independent mechanisms, which are automorphism breaking of the pattern graph, initial pattern vertex selection based on a cost model  ...  PARALLEL SUBGRAPH LISTING FRAME-WORK The Parallel Subgraph Listing (PSgL) framework follows the state-of-the-art graph processing paradigm [21] , which applies the vertex-centric programming model and  ... 
doi:10.1145/2588555.2588557 dblp:conf/sigmod/ShaoCCMYX14 fatcat:6uoiyaydu5gylg7wru4dmahwnm
Citation

Yingxia Shao, Bin Cui, Lei Chen, Lin Ma, Junjie Yao, Ning Xu. "Parallel subgraph listing in a large-scale graph." Proceedings of the 2014 ACM SIGMOD international conference on Management of data - SIGMOD '14 (2014) 625-636

Comparison of Graph-based Model Transformation Rules

Alexander Schultheiß, Alexander Boll, Timo Kehrer
2020 Journal of Object Technology  

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To validate this research hypothesis, the paper makes the following contributions: • An approach to use maximum common subgraph algorithms for comparing graph-based transformation rules, including an analysis  ...  Focusing on rule-based model transformations based on graph transformation concepts, we propose to compare such transformation rules using a maximum common subgraph (MCS) algorithm as the underlying matching  ...  Graphs, graph morphisms and maximum common subgraphs As usual in MDE, we consider models as typed graphs whose types are drawn from a meta-model.  ... 
doi:10.5381/jot.2020.19.2.a3 fatcat:uciewbresndetm7zxhcyh5kiyq
Open Access
Citation

Alexander Schultheiß, Alexander Boll, Timo Kehrer. "Comparison of Graph-based Model Transformation Rules." Journal of Object Technology 19.2 (2020) 3:1

TurboGraph

Wook-Shin Han, Sangyeon Lee, Kyungyeol Park, Jeong-Hoon Lee, Min-Soo Kim, Jinha Kim, Hwanjo Yu
2013 Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13  

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Although distributed graph engines such as GBase and Pregel handle billion-scale graphs, the user needs to be skilled at managing and tuning a distributed system in a cluster, which is a nontrivial job  ...  Graphs are used to model many real objects such as social networks and web graphs.  ...  Distributed asynchronous approaches: GraphLab [16] is also based on the vertex-centric programming model but a vertex kernel is executed in asynchronous parallel on each vertex.  ... 
doi:10.1145/2487575.2487581 dblp:conf/kdd/HanLPL0KY13 fatcat:wm3oy6qgdfh4hgo5ma2ygcrtc4
Citation

Wook-Shin Han, Sangyeon Lee, Kyungyeol Park, Jeong-Hoon Lee, Min-Soo Kim, Jinha Kim, Hwanjo Yu. "TurboGraph." Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '13 (2013) 77-85

Gunrock: GPU Graph Analytics [article]

Yangzihao Wang, Yuechao Pan, Andrew Davidson, Yuduo Wu, Carl Yang, Leyuan Wang, Muhammad Osama, Chenshan Yuan, Weitang Liu, Andy T. Riffel and John D. Owens
2017 arXiv   pre-print

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to quickly develop new graph primitives with small code size and minimal GPU programming knowledge.  ...  Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers  ...  Thanks to the Altair and Vega-lite teams in the Interactive Data Lab at the University of Washington for graphing help. Joe Mako provided the speedup chart design.  ... 
arXiv:1701.01170v1 fatcat:kgx3yuxsrzegvkbo6x7tz5jbba
Open Access
Citation

Yangzihao Wang, Yuechao Pan, Andrew Davidson, Yuduo Wu, Carl Yang, Leyuan Wang, Muhammad Osama, Chenshan Yuan, Weitang Liu, Andy T. Riffel and John D. Owens. "Gunrock: GPU Graph Analytics." arXiv (2017)

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