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- W2172051569 abstract "Agglomerative clustering is an effective greedy way to quickly generate graph clusterings of high modularity in a small amount of time. In an effort to use the power offered by multi-core CPU and GPU hardware to solve the clustering problem, we introduce a fine-grained sharedmemory parallel graph coarsening algorithm and use this to implement a parallel agglomerative clustering heuristic on both the CPU and the GPU. This heuristic is able to generate clusterings in very little time: a modularity 0.996 clustering is obtained from a street network graph with 14 million vertices and 17 million edges in 4.6 seconds on the GPU." @default.
- W2172051569 created "2016-06-24" @default.
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- W2172051569 date "2013-01-01" @default.
- W2172051569 modified "2023-09-26" @default.
- W2172051569 title "Graph coarsening and clustering on the GPU" @default.
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- W2172051569 doi "https://doi.org/10.1090/conm/588/11706" @default.
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