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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)  
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

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)  
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

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  
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

Big Graph Mining: Frameworks and Techniques

Sabeur Aridhi, Engelbert Mephu Nguifo
2016 Big Data Research  
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

BLADYG: A Graph Processing Framework for Large Dynamic Graphs

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

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

Siddharth D Jaiswal, Yogesh Simmhan
2019 arXiv   pre-print
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

Efficient snapshot retrieval over historical graph data

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

Towards Balance-Affinity Tradeoff in Concurrent Subgraph Traversals

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

Storing and Analyzing Historical Graph Data at Scale [article]

Udayan Khurana, Amol Deshpande
2015 arXiv   pre-print
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

Link mining

Lise Getoor, Christopher P. Diehl
2005 SIGKDD Explorations  
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

ICDE conference 2015 detailed author index

2015 2015 IEEE 31st International Conference on Data Engineering  
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

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  
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

Comparison of Graph-based Model Transformation Rules

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

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  
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

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
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
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