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kmcudaR (version 1.1.0)

'Yingyang' K-Means and K-NN using NVIDIA CUDA

Description

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.

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Version

Install

install.packages('kmcudaR')

Monthly Downloads

2

Version

1.1.0

License

Apache License (>= 2.0) | file LICENSE

Maintainer

Charles Jr

Last Published

March 22nd, 2019

Functions in kmcudaR (1.1.0)

kmeans_cuda

K-Means Clustering using CUDA
knn_cuda

K-Nearest Neighbor Classification using CUDA