# (Semi-)External Algorithms for Graph Partitioning and Clustering

@inproceedings{Akhremtsev2015SemiExternalAF, title={(Semi-)External Algorithms for Graph Partitioning and Clustering}, author={Yaroslav Akhremtsev and Peter Sanders and Christian Schulz}, booktitle={ALENEX}, year={2015} }

In this paper, we develop semi-external and external memory algorithms for graph partitioning and clustering problems. Graph partitioning and clustering are key tools for processing and analyzing large complex networks. We address both problems in the (semi-)external model by adapting the size-constrained label propagation technique. Our (semi-)external size-constrained label propagation algorithm can be used to compute graph clusterings and is a prerequisite for the (semi-)external graph…

## 13 Citations

### Parallel and External High Quality Graph Partitioning

- Computer Science
- 2019

First, this work presents an approach to shared-memory parallel multi-level graph partitioning that guarantees balanced solutions, shows high speed-ups for a variety of large graphs and yields very good quality independently of the number of cores used.

### Parallel Graph Partitioning for Complex Networks

- Computer ScienceIEEE Transactions on Parallel and Distributed Systems
- 2017

This work parallelizes and adapts the label propagation technique originally developed for graph clustering and becomes applicable for both the coarsening and the refinement phase of multilevel graph partitioning, and obtains very high quality by applying a highly parallel evolutionary algorithm to the coARSest graph.

### Label Propagation for Hypergraph Partitioning

- Computer Science
- 2015

This thesis investigates the adaptation of label propagation, a graph clustering algorithm, to hypergraph partitioning and proposes three adaptations oflabel propagation which are motivated by graph-based hypergraph modeling and evaluates them as coarsening strategies in a direct k-way multilevel hyper- graph partitioning framework.

### GraphMP: An Efficient Semi-External-Memory Big Graph Processing System on a Single Machine

- Computer Science2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS)
- 2017

This paper proposes GraphMP, a vertex-centric sliding window computation model to avoid reading and writing vertices on disk, and uses a compressed edge cache mechanism to fully utilize the available memory of a machine to reduce the amount of disk accesses for edges.

### Practical Minimum Cut Algorithms

- Computer ScienceALENEX
- 2018

This work introduces a linear-time algorithm to compute near-minimum cuts based on cluster contraction using label propagation and Padberg and Rinaldi’s contraction heuristics and achieves a lower running time and better parallel scalability at the expense of a higher error rate.

### Scalable Graph Algorithms

- Computer ScienceArXiv
- 2019

This habilitation thesis is a summary a broad spectrum of scalable graph algorithms that I developed over the last six years with many coauthors based on four pillars: multilevel algorithms, practical kernelization, parallelization and memetic algorithms that are highly interconnected.

### I/O-Efficient Generation of Massive Graphs Following the LFR Benchmark

- Computer ScienceALENEX
- 2017

EM-LFR is presented, the first external memory algorithm able to generate massive complex networks following the LFR benchmark and evidence that both implementations yield graphs with matching properties by applying clustering algorithms to generated instances is given.

### Graph Clustering using MapReduce

- 2017

Detecting community structures in networks is an important problem in graph analytics. With the recent BigData trends network sizes are growing tremendously. Oftentimes the networks are now too big…

### A Critical Survey of the Multilevel Method in Complex Networks

- Computer ScienceACM Comput. Surv.
- 2020

An extensive survey of the literature is presented, presenting a systematic overview of the state-of-the-art, a panorama of the historical evolution and current challenges, and a formal theoretical framework of the multilevel optimization method in complex networks.

### Hardware Locality-Aware Partitioning and Dynamic Load-Balancing of Unstructured Meshes for Large-Scale Scientific Applications

- Computer SciencePASC
- 2020

An open-source topology-aware hierarchical unstructured mesh partitioning and load-balancing tool TreePart, successfully integrated into the authors' in-house code and results from a large-eddy simulation of a combustion problem are presented.

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