gpuHclust: Perform Hierarchical Clustering for Vectors with a GPU
In gputools: A Few GPU Enabled Functions

Description Usage Arguments Value See Also Examples

This function performs clustering on a set of points. The distance between each pair of points should be calculated first using a function like 'gpuDist' or 'dist'.

1	gpuHclust(distances, method = "complete")

`distances`	a class of type "dist" containing floating point numbers representing distances between points. R's native dist function and the gpuDist function produce output of this type.
`method`	a string representing the name of the clustering method to be applied to distances. Currently supported method names include "average", "centroid", "complete", "flexible", "flexible group", "mcquitty", "median", "single", "ward", and "wpgma".

Copied from the native R function 'hclust' documentation. A class of type "hclust" with the following attributes.

`merge`	an n-1 by 2 matrix. Row i of 'merge' describes the merging of clusters at step i of the clustering. If an element j in the row is negative, then observation -j was merged at this stage. If j is positive then the merge was with the cluster formed at the (earlier) stage j of the algorithm. Thus negative entries in 'merge' indicate agglomerations of singletons, and positive entries indicate agglomerations of non-singletons. Copied from the native R function 'hclust' documentation.
`order`	a vector giving the permutation of the original observations suitable for plotting, in the sense that a cluster plot using this ordering and matrix 'merge' will not have crossings of the branches.
`height`	a set of n-1 non-decreasing real values. The clustering height: that is, the value of the criterion associated with the clustering 'method' for the particular agglomeration.

hclust, gpuDistClust

numVectors <- 5
dimension <- 10
Vectors <- matrix(runif(numVectors*dimension), numVectors, dimension)
distMat <- gpuDist(Vectors, "euclidean")
myClust <- gpuHclust(distMat, "single")
plot(myClust)