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

Package details

AuthorVadim Markovtsev, Charles Determan
MaintainerCharles Determan <>
LicenseApache License (>= 2.0) | file LICENSE
Package repositoryView on CRAN
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kmcudaR documentation built on May 2, 2019, 9:17 a.m.