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kmcudaR: 'Yingyang' K-Means and K-NN using NVIDIA CUDA
K-means implementation is base on "Yingyang K-Means: A Drop-In Replacement of the Classic K-Means with Consistent Speedup". While it introduces some overhead and many conditional clauses which are bad for CUDA, it still shows 1.6-2x speedup against the Lloyd algorithm. K-nearest neighbors employ the same triangle inequality idea and require precalculated centroids and cluster assignments, similar to the flattened ball tree.
Getting started
Browse package contents
Package details |
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| Author | Vadim Markovtsev, Charles Determan |
| Maintainer | Charles Determan <cdetermanjr@gmail.com> |
| License | Apache License (>= 2.0) | file LICENSE |
| Version | 1.1.0 |
| Package repository | View on CRAN |
| Installation |
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