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2011 Jan 29
0
Parallelizing cor() for large data-set using Cluster
...can find cl = cor(cdata) utilizing the computers in the clusters(I am using 32 nodes ). I am using the following code to get the cluster.. library(snow) cl <- makeCluster(64) clusterExport(cl, "fakeData") clusterEvalQ(cl, library(boot)) system.time(out2 <- clusterApplyLB(cl, pair, geneCor)) stopCluster(cl) But here the geneCor and pair is calculated as, pair <- combn(1:nrow(fakeData), 2, simplify = F) geneCor <- function(x, gene = fakeData) { cor(t(gene[x[1], ]), t(gene[x[2], ])) } #This calculates for each pairs. But I want cor(data) for a 2D matrix to be parallelized. reg...