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# Less inefficient parallel matrix multiply using custom matrix iterator
library(foreach)
iblkcol <- function(a, chunks) {
n <- ncol(a)
i <- 1
nextEl <- function() {
if (chunks <= 0 || n <= 0) stop('StopIteration')
m <- ceiling(n / chunks)
r <- seq(i, length=m)
i <<- i + m
n <<- n - m
chunks <<- chunks - 1
a[,r, drop=FALSE]
}
obj <- list(nextElem=nextEl)
class(obj) <- c('abstractiter', 'iter')
obj
}
# generate the input matrices
x <- matrix(rnorm(100), 10)
y <- matrix(rnorm(100), 10)
# multiply the matrices
nw <- getDoParWorkers()
cat(sprintf('Running with %d worker(s)\n', nw))
mit <- iblkcol(y, nw)
z <- foreach(y=mit, .combine=cbind) %dopar% (x %*% y)
# print the results
print(z)
# check the results
print(all.equal(z, x %*% y))
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