[R] CPU or memory
Prof Brian Ripley
ripley at stats.ox.ac.uk
Thu Nov 9 08:34:54 CET 2006
On Wed, 8 Nov 2006, Liaw, Andy wrote:
> 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.
In most cases I am aware of those 64-bit chips will run 32-bit code faster
than 64-bit code, just because there is less data (memory addresses) to
move around and in particular that more addresses fit into the caches. It
is true for example on both Solaris and AMD64 CPUs that a 32-bit compile
of R runs 10-20% faster than a 64-bit compile. (As I recall, Itanium is
different.)
> 64-bit PCs should be really affordable: I've seen HP laptops based on
> the Turion chip selling below $500US.
You may want to run a 32-bit OS (or compile 32-bit applications) on them,
unless you have a lot of RAM (more than 2Gb) and large applications.
> 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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>
--
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
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