Multi-threads in R

Dear R users,

I'm wonder if there is a easy way to make R use multi-CPUs on my computer.
My computer has four CPUs but R uses only one. Thanks.

Gary

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Take a look at the parallel package which ships with all current versions of R.

Michael

On Jun 17, 2012, at 11:39 AM, Gary Dong<pdxgary163 at gmail.com>  wrote:

Dear R users,

I'm wonder if there is a easy way to make R use multi-CPUs on my computer.
My computer has four CPUs but R uses only one. Thanks.

Gary

    [[alternative HTML version deleted]]

Thanks for all replied.

I read the introduction of R parallel. Is it for loops only?

Gary


On Sun, Jun 17, 2012 at 10:04 AM, R. Michael Weylandt
<michael.weylandt at gmail.com> <michael.weylandt at gmail.com> wrote:

Take a look at the parallel package which ships with all current versions
of R.

Michael

On Jun 17, 2012, at 11:39 AM, Gary Dong <pdxgary163 at gmail.com> wrote:

Dear R users,

I'm wonder if there is a easy way to make R use multi-CPUs on my
computer.
My computer has four CPUs but R uses only one. Thanks.

Gary

? ?[[alternative HTML version deleted]]

I would argue (somewhat emphatically) that the parallel facilities you
are looking at are absolutely not for `for` loops. `for` loops are a
control structure native to imperative programming and, as such, are
inherently stateful. This provides many advantages, but easy
parallelization is absolutely not one of them. Rather consider R as a
functional language and the appropriate "control structure" is the
Map(), most famously of MapReduce, but also inherent in R's *apply()
family of functions. The careful reader will note that here is where
parallelization is exposed. By being state-free, there's no inherent
sequentiality and, consequently, no barriers to parallel computing.

For a somewhat concrete example consider what it would take to do a
state-dependent simulation (like a gibbs sampler) in parallel: it is,
to my mind, quite non-trivial. Compare this to the question of doing
column sums of a matrix in parallel -- effectively trivial. The
parallelization afforded by R is of that second sort.

A red herring in this discussion is the foreach() formalism, but a
moment's thought suggests to me that foreach() is much closer to Map()
than to for().

Best,
Michael

On Sun, Jun 17, 2012 at 1:23 PM, Gary Dong <pdxgary163 at gmail.com> wrote:

Thanks for all replied.

I read the introduction of R parallel. Is it for loops only?

Gary


On Sun, Jun 17, 2012 at 10:04 AM, R. Michael Weylandt
<michael.weylandt at gmail.com> <michael.weylandt at gmail.com> wrote:

Take a look at the parallel package which ships with all current versions
of R.

Michael

On Jun 17, 2012, at 11:39 AM, Gary Dong <pdxgary163 at gmail.com> wrote:

Dear R users,

I'm wonder if there is a easy way to make R use multi-CPUs on my
computer.
My computer has four CPUs but R uses only one. Thanks.

Gary

? ?[[alternative HTML version deleted]]