Thanks a lot Simon, that's useful.
I will take a look at this process-pinning things.

Arnaud


2013/10/28 Simon Zehnder <szehnder@uni-bonn.de>

> First,
>
> use only the number of cores as a number of thread - i.e. I would not use
> hyper threading, etc.. Each core has its own caches and it is always
> fortunate if a process has enough memory; hyper threads use all the same
> cache on the core they are running on. detectCores() gives me for example 4
> - I know I have 2. I would therefore call makeCluster() with nnode = 2.
> mcaffinity() lets you perform a technique called process-pinning (see
> process affinity) and is only possible if the OS supports it. It makes
> sometimes sense to assign certain processes to certain CPUs such that each
> process has enough memory in caches (e.g. for a 16 Core machine using 8
> processes on CPUs 1, 3, 5, 7, 9, 11, 13 and 15; so each process has the
> cache of two CPUs).
> A lot of functions though are not available for Windows.
>
> At first it comes always the problem you want to solve and then you look
> how much memory will be used in a process and how much you have (more often
> the memory bandwidth is the bottleneck and not the computing power). Look
> at the architecture of your chips (how much L1 Cache, how much L2 cache).
> Then you decide how many cores to use and if it makes sense to pin
> processes to certain cores.
>
> There are no general recipes for parallel computing - each problem is
> different. Some problems are even not scalable.
>
> Simon
>
>
> On 28 Oct 2013, at 17:51, Arnaud Mosnier <a.mosnier@gmail.com> wrote:
>
> > Thanks Simon,
> >
> > I already read the parallel vignette but I did not found what I wanted.
> > May be you can be more specific on a part of the document that can
> provide me hints !
> >
> > Arnaud
> >
> >
> > 2013/10/28 Simon Zehnder <szehnder@uni-bonn.de>
> > See library(help = "parallel”)
> >
> >
> > On 28 Oct 2013, at 17:19, Arnaud Mosnier <a.mosnier@gmail.com> wrote:
> >
> > > Hi all,
> > >
> > > I am quite new in the world of parallelization and I wonder if there
> is a
> > > way to increase the speed of creation of a parallel socket cluster. The
> > > time spend to include threads increase exponentially with the number of
> > > thread considered and I use of computer with two 8 cores CPU and thus
> > > showing a total of 32 threads in windows 7.
> > > Currently, I use the default parameters (type = "PSOCK"), but is there
> any
> > > fine tuning parameters that I can use to take advantage of this system
> ?
> > >
> > > Thanks in advance for your help !
> > >
> > > Arnaud
> > >
> > > R version 3.0.1 (2013-05-16)
> > > Platform: x86_64-w64-mingw32/x64 (64-bit)
> > >
> > >       [[alternative HTML version deleted]]
> > >
> > > ______________________________________________
> > > R-help@r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> > > and provide commented, minimal, self-contained, reproducible code.
> >
> >
>
>

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