[R] CPU or memory
Liaw, Andy
andy_liaw at merck.com
Thu Nov 9 02:58:28 CET 2006
My understanding is that it doesn't have much to do with 32- vs. 64-bit,
but what the instruction sets of the CPUs. If I'm not mistaken, at the
same clock speed, a P4 would run slower than PIII simply because P4 does
less per clock-cycle. Also, I believe for the same architecture, single
core chips are available at higher clock speeds than their multi-core
counterparts. That's why we recently went for a box with four
single-core Opterons instead of two dual-core ones.
64-bit PCs should be really affordable: I've seen HP laptops based on
the Turion chip selling below $500US.
Andy
From: John C Frain
>
> I would like to thank all who replied to my question about
> the efficiency of various cpu's in R.
>
> Following the advice of Bogdan Romocea I have put a sample
> simulation and the latest version of R on a USB drive and
> will go to a few suppliers to try it out. I will report back
> if I find anything of interest.
>
> With regard to 64-bit and 32-bit I thought that the 64-bit
> chip might require less clock cycles for a specific machine
> instruction than a 32-bit.
> This was one of the advantages of moving from 8 to 16 or from
> 16 to 32 bit chips. Thus a slower, in terms of clock speed,
> 64-bit chip might run faster than a somewhat similar 32-bit
> chip. I fully realize that the full advantage of a 64-bit
> chip is available only with a 64-bit operating system and I
> am preparing to switch some work to Linux in case I acquire a
> 64-bit PC. If I do I will time the simulations on that also.
>
> I already do some "coarse-grained parallelism" as described
> by *Brian Ripley
> * but on two separate PC's. This is not ideal but allows the
> processing time to be halved without the overheads.
>
> FORTRAN 2 was my first programming language and I agree that
> I should try to use C or FORTRAN to speed up things. Finally
> Rprof could be a great help.
> There are lots of utilities in the utils package with which I
> was not familiar.
>
> Again Many Thanks to all who made various suggestions.
>
>
> bogdan romocea <br44114 at gmail.com> to *r-help*, me
> More options 07-Nov (1 day ago) > Does any one know of
> comparisons of
> the Pentium 9x0, Pentium(r)
> > Extreme/Core 2 Duo, AMD(r) Athlon(r) 64 , AMD(r) Athlon(r)
> 64 FX/Dual
> > Core AM2 and similar chips when used for this kind of work.
>
>
>
> On 08/11/06, Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote:
> >
> > On Wed, 8 Nov 2006, Christos Hatzis wrote:
> >
> > > Prof. Ripley,
> > >
> > > Do you mind providing some pointers on how
> "coarse-grained parallelism"
> > > could be implemented on a Windows environment? Would it be as
> > > simple as running two R-console sessions and then (manually)
> > > combining the results
> > of
> > > these simulations. Or it would be better to run them as batch
> > processes.
> >
> > That is what I would do in any environment (I don't do such things
> > under Windows since all my fast machines run Linux/Unix).
> >
> > Suppose you want to do 10000 simulations. Set up two batch scripts
> > that each run 5000, and save() the results as a list or
> matrix under
> > different names, and set a different seed at the top. Then
> run each
> > via R CMD BATCH simultaneously. When both have finished, use an
> > interactive session to load() both sets of results and merge them.
> >
> > > RSiteSearch('coarse grained') did not produce any hits so
> this topic
> > might
> > > have not been discussed on this list.
> > >
> > > I am not really familiar with running R in any mode other than the
> > default
> > > (R-console in Windows) so I might be missing something really
> > > obvious. I
> > am
> > > interested in running Monte-Carlo cross-validation in
> some sort of a
> > > parallel mode on a dual core (Pentium D) Windows XP machine.
> > >
> > > Thank you.
> > > -Christos
> > >
> > > Christos Hatzis, Ph.D.
> > > Nuvera Biosciences, Inc.
> > > 400 West Cummings Park
> > > Suite 5350
> > > Woburn, MA 01801
> > > Tel: 781-938-3830
> > > www.nuverabio.com
> > >
> > >
> > >
> > > -----Original Message-----
> > > From: r-help-bounces at stat.math.ethz.ch
> > > [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Prof Brian
> > > Ripley
> > > Sent: Wednesday, November 08, 2006 5:29 AM
> > > To: Stefan Grosse
> > > Cc: r-help at stat.math.ethz.ch; Taka Matzmoto
> > > Subject: Re: [R] CPU or memory
> > >
> > > On Wed, 8 Nov 2006, Stefan Grosse wrote:
> > >
> > >> 64bit does not make anything faster. It is only of use
> if you want
> > >> to use more then 4 GB of RAM of if you need a higher
> precision of
> > >> your variables
> > >>
> > >> The dual core question: dual core is faster if programs
> are able to
> > >> use that. What is sure that R cannot make (until now) use of the
> > >> two cores if you are stuck on Windows. It works excellent if you
> > >> use Linux. So if you want dual core you should work with
> linux (and
> > >> then its faster of course).
> > >
> > > Not necessarily. We have seen several examples in which using a
> > > multithreaded BLAS (the only easy way to make use of
> multiple CPUs
> > > under Linux for a single R process) makes things many
> times slower.
> > > For tasks that are do not make heavy use of linear algebra, the
> > > advantage of a multithreaded BLAS is small, and even from those
> > > which do the speed-up
> > is
> > > rarely close to double for a dual-CPU system.
> > >
> > > John mentioned simulations. Often by far the most
> effective way to
> > > use
> > a
> > > multi-CPU platform (and I have had one as my desktop for over a
> > > decade)
> > is
> > > to use coarse-grained parallelism: run two or more processes each
> > > doing
> > some
> > > of the simulation runs.
> > >
> > >> The Core 2 duo is the fastest processor at the moment however.
> > >>
> > >> (the E6600 has a good price/performance ration)
> > >>
> > >> What I already told Taka is that it is probably always a
> good idea
> > >> to improve your code for which purpose you could ask in this
> > >> mailing list... (And I am very sure that you have there
> a lot of potential).
> > >> Another speeding up possibility is e.g. using the atlas
> library...
> > >> (where I am not sure if you already use it)
> > >>
> > >> Stefan
> > >>
> > >> John C Frain schrieb:
> > >>> *Can I extend Taka's question?*
> > >>> **
> > >>> *Many of my programs in (mainly simulations in R which are cpu
> > >>> bound) on a year old PC ( Intel(R) Pentium(R) M
> processor 1.73GHz
> > >>> or Dell GX380 with 2.8Gh Pentium) are taking hours and perhaps
> > >>> days to complete on a one year old PC. I am looking at
> an upgrade
> > >>> but the variety of cpu's available is
> > >>> confusing at least. Does any one know of comparisons
> of the Pentium
> > >>> 9x0, Pentium(r)
> > >>> Extreme/Core 2 Duo, AMD(r) Athlon(r) 64 , AMD(r) Athlon(r) 64
> > >>> FX/Dual Core AM2 and
> > >>> similar chips when used for this kind of work. Does
> anyone have
> > >>> any advice on (1) the use of a single core or dual core cpu or
> > >>> (2) on the use of 32 bit and 64 bit cpu. This question is now
> > >>> much more difficult as the numbers on the various chips do not
> > >>> necessarily refer to the relative speed of the chips.
> > >>> *
> > >>> *John
> > >>>
> > >>> * On 06/11/06, Taka Matzmoto <sell_mirage_ne at hotmail.com> wrote:
> > >>>
> > >>>
> > >>>> Hi R users
> > >>>>
> > >>>> Having both a faster CPU and more memory will boost
> computing power.
> > >>>> I was wondering if only adding more memory (1GB -> 2GB) will
> > >>>> significantly reduce R computation time?
> > >>>>
> > >>>> Taka,
> > >>>>
> > >>>>
> _________________________________________________________________
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> > >>>>
> > >>>> ______________________________________________
> > >>>> R-help at stat.math.ethz.ch 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.
> > >>>>
> > >>>>
> > >>>
> > >>>
> > >>>
> > >>>
> > >>
> > >> ______________________________________________
> > >> R-help at stat.math.ethz.ch 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.
> > >>
> > >
> > >
> >
> > --
> > 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)
> > 1 South Parks Road, +44 1865 272866 (PA)
> > Oxford OX1 3TG, UK Fax: +44 1865 272595
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch 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.
> >
>
>
>
> --
> John C Frain
> Trinity College Dublin
> Dublin 2
> Ireland
> www.tcd.ie/Economics/staff/frainj/home.html
> mailto:frainj at tcd.ie
> mailto:frainj at gmail.com
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at stat.math.ethz.ch 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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