Designing Network Immunization Strategies Based on Graph Partitioning Methods

Author(s):  
Changxi Niu ◽  
Lemin Li ◽  
Du Xu
Author(s):  
Hristo N. Djidjev ◽  
Georg Hahn ◽  
Susan M. Mniszewski ◽  
Christian F.A. Negre ◽  
Anders M.N. Niklasson ◽  
...  

2011 ◽  
Author(s):  
Abhinav Bhatele ◽  
Sebastien Fourestier ◽  
Harshitha Menon ◽  
Laxmikant V. Kale ◽  
Francois Pellegrini

2016 ◽  
Author(s):  
Hristo Nikolov Djidjev ◽  
Georg Hahn ◽  
Susan M. Mniszewski ◽  
Christian Francisco Negre ◽  
Anders Mauritz Niklasson ◽  
...  

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yun Hao ◽  
Gaofeng Li ◽  
Pingpeng Yuan ◽  
Hai Jin ◽  
Xiaofeng Ding

The volumes of real-world graphs like knowledge graph are increasing rapidly, which makes streaming graph processing a hot research area. Processing graphs in streaming setting poses significant challenges from different perspectives, among which graph partitioning method plays a key role. Regarding graph query, a well-designed partitioning method is essential for achieving better performance. Existing offline graph partitioning methods often require full knowledge of the graph, which is not possible during streaming graph processing. In order to handle this problem, we propose an association-oriented streaming graph partitioning method named Assc. This approach first computes the rank values of vertices with a hybrid approximate PageRank algorithm. After splitting these vertices with an adapted variant affinity propagation algorithm, the process order on vertices in the sliding window can be determined. Finally, according to thelevelof these vertices and their association, the partition where the vertices should be distributed is decided. We compare its performance with a set of streaming graph partition methods and METIS, a widely adopted offline approach. The results show that our solution can partition graphs with hundreds of millions of vertices in streaming setting on a large collection of graph datasets and our approach outperforms other graph partitioning methods.


2019 ◽  
Vol 38 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Nasrin Mazaheri Soudani ◽  
Afsaneh Fatemi ◽  
Mohammadali Nematbakhsh

2010 ◽  
Vol 60 (4) ◽  
pp. 611-633 ◽  
Author(s):  
Matías Toril ◽  
Iñigo Molina-Fernández ◽  
Volker Wille ◽  
Chris Walshaw

Author(s):  
Е.Н. Головченко ◽  
М.В. Якобовский

Задача рациональной декомпозиции расчетных сеток возникает при численном моделировании на высокопроизводительных вычислительных системах проблем механики сплошных сред, импульсной энергетики, электродинамики и др. Число процессоров, на котором будет считаться вычислительная задача, как правило, заранее не известно. В этой связи имеет смысл предварительно однократно разбить сетку на большое число микродоменов, а затем формировать из них домены. Методы разбиения графов параллельных пакетов ParMETIS, Jostle, PT-Scotch и Zoltan основываются на иерархических алгоритмах, недостатком которых является образование несвязных доменов. Другим недостатком указанных пакетов является получение сильно несбалансированных разбиений. Разработан пакет программ GridSpiderPar для параллельной декомпозиции больших сеток. Проведены вычислительные эксперименты по сравнению различных разбиений на микродомены, разбиений графов микродоменов на домены, а также разбиений сразу на домены нескольких сеток ($10^8$ вершин, $10^9$ элементов), полученных методами созданного комплекса программ GridSpiderPar и пакетов ParMETIS, Zoltan и PT-Scotch. Качество разбиений проверялось по дисбалансу числа вершин в доменах, числу несвязных доменов и числу разрезанных ребер, а также по эффективности параллельного счета задач газовой динамики при распределении сеток по ядрам в соответствии с различными разбиениями. Полученные результаты выявили преимущества разработанных алгоритмов. The problem of load balancing arises in parallel mesh-based numerical solution of problems of continuum mechanics, energetics, electrodynamics etc. on high-performance computing systems. The number of processors to run a computational problem is often unknown. It makes sense, therefore, to partition a mesh into a great number of microdomains which then are used to create subdomains. Graph partitioning methods implemented in state-of-the-art parallel partitioning tools ParMETIS, Jostle, PT-Scotch and Zoltan are based on multilevel algorithms. That approach has a shortcoming of forming unconnected subdomains. Another shortcoming of present graph partitioning methods is generation of strongly imbalanced partitions. The program package for parallel large mesh decomposition GridSpiderPar was developed. We compared different partitions into microdomains, microdomain graph partitions and partitions into subdomains of several meshes (10^8 vertices, 10^9 elements) obtained by means of the partitioning tool GridSpiderPar and the packages ParMETIS, Zoltan and PT-Scotch. Balance of the partitions, edge-cut and number of unconnected subdomains in different partitions were compared as well as the computational performance of gas-dynamic problem simulations run on different partitions. The obtained results demonstrate advantages of the proposed algorithms.


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