[R] mcapply not using more than 1 core

[Prof Brian Ripley]

On 28/08/2013 06:54, joe meiring wrote:
> This does speed up on an OsX install, so something must be wacky with the
> linux install. Any ideas as to what would cause this?

It does on a Linux platform ('install' has nothing to do with this):

 > system.time(x <- lapply(test,function(x) loess.smooth(x,x)))
    user  system elapsed
   4.095   0.036   4.140

 > system.time(x <- mclapply(test,function(x) loess.smooth(x,x), 
mc.cores=24))
    user  system elapsed
   8.125   0.639   0.563

What is odd is that no CPU time is being recorded in the original posting.

That is about what I would expect: there is an overhead in forking 24 
processes and this example is too small to be realistic.

>
> On Tuesday, August 27, 2013 4:19:31 PM UTC-7, joe meiring wrote:
>>
>> I can't seem to get mclapply to use more than a single core. I have a 64
>> core server running Linux.
>>
>> Fore example:
>>
>> library(parallel)
>>
>> test <- lapply(1:100,function(x) rnorm(10000))
>> system.time(x <- lapply(test,function(x) loess.smooth(x,x)))
>> system.time(x <- mclapply(test,function(x) loess.smooth(x,x),
>> mc.cores=32))
>>
>> gives me:
>>
>>     user  system elapsed
>>    0.000   0.000   7.441
>>     user  system elapsed
>>    0.000   0.000   8.868
>>
>> i.e. mclapply is taking longer than lapply(). What is going wrong here?
>>
>>          [[alternative HTML version deleted]]
>>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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