fastcorr.R

mini <- matrix(rnorm(4000*50), nrow=4000, ncol=50)
system.time(M <- cor(t(mini), t(mini), method='pearson'))

fastcorr <- function(x) {
	# fast correlation between rows of x
	# from http://stackoverflow.com/questions/18964837/fast-correlation-in-r-using-c-and-parallelization
	if (!is.matrix(x)) x <- as.matrix(x)
	x <- x - rowMeans(x)
	x <- x/sqrt(rowSums(x^2))
	tcrossprod(x)
}
system.time(M2 <- fastcorr(mini))
all.equal(M, M2)		# fastcorr is significantly faster. Even better if you compile R using fast BLAS