Filters








2,228 Hits in 6.3 sec

Partitioning Complex Networks via Size-constrained Clustering [article]

Henning Meyerhenke and Peter Sanders and Christian Schulz
2014 arXiv   pre-print
More precisely, our algorithm provides graph coarsening by iteratively contracting size-constrained clusterings that are computed using a label propagation algorithm.  ...  During a coarsening phase, a multilevel graph partitioning algorithm reduces the graph size by iteratively contracting nodes and edges until the graph is small enough to be partitioned by some other algorithm  ...  It includes KaFFPa (Karlsruhe Fast Flow Partitioner), which is a matching-based multilevel graph partitioning framework that uses for example flow-based methods and more-localized local searches to compute  ... 
arXiv:1402.3281v2 fatcat:2ecuaiu2pnf7hpglaieo57g4ey

Parallel Graph Partitioning for Complex Networks [article]

Henning Meyerhenke, Peter Sanders, Christian Schulz
2015 arXiv   pre-print
By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning.  ...  This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering.  ...  Moreover, we would like to thank Horst Gernert and his team for the support that we received while we performed the scalability experiments on the cluster.  ... 
arXiv:1404.4797v3 fatcat:p7tgz4xej5cj3lghbx6qaltan4

Parallel Graph Partitioning for Complex Networks

Henning Meyerhenke, Peter Sanders, Christian Schulz
2017 IEEE Transactions on Parallel and Distributed Systems  
By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning.  ...  This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering.  ...  Moreover, we would like to thank Horst Gernert and his team for the support that we received while we performed the scalability experiments on the cluster.  ... 
doi:10.1109/tpds.2017.2671868 fatcat:wpbh6bp5pnfcdkxjteppwxv7di

Parallel Graph Partitioning for Complex Networks

Henning Meyerhenke, Peter Sanders, Christian Schulz
2015 2015 IEEE International Parallel and Distributed Processing Symposium  
By introducing size constraints, label propagation becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning.  ...  This paper addresses this problem by parallelizing and adapting the label propagation technique originally developed for graph clustering.  ...  Moreover, we would like to thank Horst Gernert and his team for the support that we received while we performed the scalability experiments on the cluster.  ... 
doi:10.1109/ipdps.2015.18 dblp:conf/ipps/MeyerhenkeS015 fatcat:svaikn6tqfhrxn5idqljdnguse

A parallel graph partitioning algorithm to speed up the large-scale distributed graph mining

ZengFeng Zeng, Bin Wu, Haoyu Wang
2012 Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining Algorithms, Systems, Programming Models and Applications - BigMine '12  
The algorithm first efficiently aggregates the large graph into a small weighted graph, and then makes a balance partitioning on the weighted graph based on a stepwise minimizing RatioCut Algorithm.  ...  Existing graph partitioning algorithms incur high computation and communication cost when applied on large distributed graphs.  ...  This is because that we use a weighted label propagation algorithm and a novel method based on stepwise minimizing Ratio-Cut. This algorithm can also be refined from the following respects.  ... 
doi:10.1145/2351316.2351325 dblp:conf/kdd/ZengWW12 fatcat:njhkucpffnc4jikyewnmxezysm

More Recent Advances in (Hyper)Graph Partitioning [article]

Ümit V. Çatalyürek, Karen D. Devine, Marcelo Fonseca Faraj, Lars Gottesbüren, Tobias Heuer, Henning Meyerhenke, Peter Sanders, Sebastian Schlag, Christian Schulz, Daniel Seemaier, Dorothea Wagner
2022 arXiv   pre-print
In particular, the survey extends the previous survey by also covering hypergraph partitioning and streaming algorithms, and has an additional focus on parallel algorithms.  ...  In recent years, significant advances have been made in the design and evaluation of balanced (hyper)graph partitioning algorithms.  ...  We would like to thank Ilya Safro for feedback and additional references on an early version of the manuscript.  ... 
arXiv:2205.13202v3 fatcat:xgz5hgqgireojelyaegrbyxoua

Deep Multilevel Graph Partitioning [article]

Lars Gottesbüren, Tobias Heuer, Peter Sanders, Christian Schulz, Daniel Seemaier
2021 arXiv   pre-print
This is because most high-quality general-purpose graph partitioners are multilevel algorithms which perform graph coarsening to build a hierarchy of graphs, initial partitioning to compute an initial  ...  For example, for large number of blocks our algorithm is on average an order of magnitude faster than competing algorithms while computing balanced partitions with comparable solution quality.  ...  Size-Constrained Label Propagation. Based on the label propagation clustering algorithm by Raghavan et al. [40] , Meyerhenke et al.  ... 
arXiv:2105.02022v1 fatcat:zzqlj2thujcync7mllt3fxtoay

PuLP: Scalable multi-objective multi-constraint partitioning for small-world networks

George M. Slota, Kamesh Madduri, Sivasankaran Rajamanickam
2014 2014 IEEE International Conference on Big Data (Big Data)  
A novel feature of our method PULP (Partitioning using Label Propagation) is that it optimizes for multiple objective metrics simultaneously, while satisfying multiple partitioning constraints.  ...  For a collection of test graphs, we show that PULP uses 8-39× less memory than state-of-the-art partitioners and is up to 14.5× faster, on average, than alternate approaches (with 16-way parallelism).  ...  As the name suggests, PULP is based on the label propagation community identification algorithm [26] .  ... 
doi:10.1109/bigdata.2014.7004265 dblp:conf/bigdataconf/SlotaMR14 fatcat:2rwfbdszyraexfhhglctredfrm

(Semi-)External Algorithms for Graph Partitioning and Clustering [article]

Yaroslav Akhremtsev, Peter Sanders, Christian Schulz
2014 arXiv   pre-print
Our (semi-)external size-constrained label propagation algorithm can be used to compute graph clusterings and is a prerequisite for the (semi-)external graph partitioning algorithm.  ...  The algorithm is then used for both the coarsening and the refinement phase of a multilevel algorithm to compute graph partitions.  ...  First of all, the semi-external and the external label propagation outperform the coloring-based clustering algorithm.  ... 
arXiv:1404.4887v2 fatcat:umgi6e6inzgr5h2wzkhn5mgzz4

Scalable Graph Algorithms [article]

Christian Schulz
2019 arXiv   pre-print
In general, this research is based on four pillars: multilevel algorithms, practical kernelization, parallelization and memetic algorithms that are highly interconnected.  ...  Designing and evaluating scalable graph algorithms to handle these data sets is a crucial task on the road to understanding the underlying systems.  ...  The initial partitioner is based on a large portfolio of simple algorithms, each with some randomization aspect (fully random, BFS, label propagation, and nine variants of greedy hypergraph growing).  ... 
arXiv:1912.00245v1 fatcat:mop2e6pqtnbr7irkrakraael6a

Dynamic Repartitioning of Adaptively Refined Meshes

K. Schloegel, G. Karypis, V. Kumar
1998 Proceedings of the IEEE/ACM SC98 Conference  
minimized, while all of the domains of a given partition contain a roughly equal amount of computational weight.  ...  On the other hand, diffusion-based schemes work well for slightly imbalanced graphs and for those in which imbalance occurs globally throughout the graph.  ...  These schemes, which we classify as either scratch-remap schemes [1, 9, 12] or diffusion-based schemes [11, 10, 13, 14] , are all based on the multilevel graph partitioning paradigm.  ... 
doi:10.1109/sc.1998.10025 dblp:conf/sc/SchloegelKK98 fatcat:4bpvwto5cbcutgozjlgbnqukia

Buffered Streaming Graph Partitioning [article]

Marcelo Fonseca Faraj, Christian Schulz
2021 arXiv   pre-print
On the other hand, there are offline (shared-memory) multilevel algorithms that produce partitions with high quality but also need a machine with enough memory.  ...  On the one hand, there are streaming algorithms that have been adopted to partition massive graph data on small machines.  ...  The algorithm to compute clusters is based on label propagation [28] and avoids large clusters by using a size constraint, as described in [22] .  ... 
arXiv:2102.09384v2 fatcat:a2nfe5sh5jdotgp7cpardlb3j4

Sampling-based Label Propagation for Balanced Graph Partitioning

Adnan El Moussawi, Ricardo Rojas Ruiz, Nacéra Bennacer Seghouani
2022 Proceedings of the 2022 ACM/SPEC on International Conference on Performance Engineering  
In this experience paper, we present new sampling-based algorithms for balanced graph partitioning based on the Label Propagation (LP) approach.  ...  The results obtained on different graphs showed that the sampling-based algorithms improve the propagation time without affecting the balance between partitions.  ...  ) = 𝑟𝑎𝑛𝑑𝑜𝑚 (𝐿) SAMPLING-BASED LABEL PROPAGATION ALGORITHMS 4.1 Main procedures One of the biggest problems in label propagation based partitioning algorithms is to deal with graphs of different  ... 
doi:10.1145/3489525.3511698 fatcat:odtmjj4npndhve6tpbnnbr2fwu

Multilevel hypergraph partitioning: applications in VLSI domain

G. Karypis, R. Aggarwal, V. Kumar, S. Shekhar
1999 IEEE Transactions on Very Large Scale Integration (vlsi) Systems  
In this paper, we present a new hypergraphpartitioning algorithm that is based on the multilevel paradigm. In the multilevel paradigm, a sequence of successively coarser hypergraphs is constructed.  ...  Index Terms-Circuit partitioning, hypergraph partitioning, multilevel algorithms.  ...  The algorithms described in this paper are part of the hMETIS hypergraphpartitioning package available via the World Wide Web at URL: http://www.cs.umn.edu/˜metis.  ... 
doi:10.1109/92.748202 fatcat:62tnubkmnzgyzmeoqc67ztbdoi

Synergistic partitioning in multiple large scale social networks

Songchang Jin, Jiawei Zhang, Philip S. Yu, Shuqiang Yang, Aiping Li
2014 2014 IEEE International Conference on Big Data (Big Data)  
Based on the given anchor nodes which exist in all the social networks and the partition results of the first network, using MapReduce, we then develop a modified distributed multilevel partitioning method  ...  In particular, we apply a distributed multilevel k-way partitioning method to divide the first network into k partitions.  ...  Inspired by the idea of local degree center based label propagation algorithm (LDC-LPA) [32] , we develop a modified LPA method to deal with the weighted nodes and weighted links in the coarsest network  ... 
doi:10.1109/bigdata.2014.7004243 dblp:conf/bigdataconf/JinZYYL14 fatcat:6hkjahfwzjfdvmnoagr56o6ufq
« Previous Showing results 1 — 15 out of 2,228 results