# What is the LSH Forest Algorithm

## LSH-Based Graph Partitioning Algorithm

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2018 | OriginalPaper | Book chapter

### Abstract

The well-partitioned graph is capable of accelerating the parallel graph algorithms significantly, but few of them adopt the well partitioning algorithms in large scale graph computing. The high time complexity, which even exceed that of the final algorithms occasionally, is the main factor to prevent their applicabilities. Existing graph partitioning algorithms are mostly based on multilevel k-way scheme or iterative label propagation. Most of these algorithms can yield a high-quality result, but the high time / space complexities limit their applications in big data. In this paper, we propose the locality-sensitive hashing (LSH) based graph partitioning algorithm whose time / space complexity is O (n), n is the number of vertices in graph. For all kinds of hyperscale graphs, it works at the speed of random partitioning method approximately. Compared with the latest mainstream graph partitioning algorithms, the new algorithm owns a simple processing pipeline and avoids irregular memory access generated by graph traversals. The experimental result show that the new algorithm achieves 10x faster than Metis and 2x faster than label propagation algorithm at the cost of reasonable precision loss.

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literature About this chapter

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Raghavan, U.N., Albert, R., Kumara, S .: Near linear time algorithm to detect community structures in large-scale networks. Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 76 (2), 036106 (2007) CrossRef Raghavan, U.N., Albert, R., Kumara, S .: Near linear time algorithm to detect community structures in large-scale networks. Phys. Rev. E Stat. Nonlinear Soft Matter Phys. 76 (2), 036106 (2007) CrossRef

- title
- LSH-Based Graph Partitioning Algorithm
- book
- Artificial Intelligence
Print ISBN: 978-981-13-2121-4

Electronic ISBN: 978-981-13-2122-1

Copyright Year: 2018

https://doi.org/10.1007/978-981-13-2122-1

- DOI
- https://doi.org/10.1007/978-981-13-2122-1_5
- Authors:
- Weidong Zhang

Mingyue Zhang - publishing company
- Springer Singapore

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