On 17/03/2012 17:03, Ken Knoblauch wrote:
I've started to use the parallel package and it works very well speeding
things up. Thank you for making this easy to do.
Should I have expected that parCapply would return a vector
when parApply returns a matrix?
Maybe: I would have expected so, and AFAICS ?parCapply does not say what
the value is so it is unspecified. We probably should document it.
library(parallel)
x <- matrix(rnorm(8), nc = 2)
apply(x, 2, function(y) y)
[,1] [,2]
[1,] -0.9649685 0.91339851
[2,] -1.4313140 0.13457671
[3,] 1.0499248 1.58967879
[4,] -1.8974411 0.03639876
cl <- makeCluster(getOption("cl.cores", detectCores()))
parApply(cl, x, 2, function(y) y)
[,1] [,2]
[1,] -0.9649685 0.91339851
[2,] -1.4313140 0.13457671
[3,] 1.0499248 1.58967879
[4,] -1.8974411 0.03639876
parCapply(cl, x, function(y) y)
[1] -0.96496852 -1.43131396 1.04992479 -1.89744113 0.91339851 0.13457671
[7] 1.58967879 0.03639876
stopCluster(cl)
sessionInfo()
R version 2.15.0 beta (2012-03-15 r58760)
Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
[8] base
Thank you.
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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