Re: [R] CPU or memory
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). 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 [EMAIL PROTECTED] 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, _ Get FREE company branded e-mail accounts and business Web site from Microsoft Office Live __ R-help@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@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.
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 [EMAIL PROTECTED] 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, _ Get FREE company branded e-mail accounts and business Web site from Microsoft Office Live __ R-help@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@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, [EMAIL PROTECTED] 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, UKFax: +44 1865 272595 __ R-help@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.
Re: [R] CPU or memory
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.
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: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Prof Brian Ripley
Sent: Wednesday, November 08, 2006 5:29 AM
To: Stefan Grosse
Cc: r-help@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 [EMAIL PROTECTED] 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,
_
Get FREE company branded e-mail accounts and business Web site from
Microsoft Office Live
__
R-help@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@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, [EMAIL PROTECTED]
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, UKFax: +44 1865 272595
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r
Re: [R] CPU or memory
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 1 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: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Prof Brian Ripley
Sent: Wednesday, November 08, 2006 5:29 AM
To: Stefan Grosse
Cc: r-help@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 [EMAIL PROTECTED] 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,
_
Get FREE company branded e-mail accounts and business Web site from
Microsoft Office Live
__
R-help@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@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R
Re: [R] CPU or memory
Great. I will try it.
Thank you.
-Christos
-Original Message-
From: Prof Brian Ripley [mailto:[EMAIL PROTECTED]
Sent: Wednesday, November 08, 2006 1:21 PM
To: Christos Hatzis
Cc: 'Stefan Grosse'; r-help@stat.math.ethz.ch; 'Taka Matzmoto'
Subject: RE: [R] CPU or memory
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 1 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: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Prof Brian
Ripley
Sent: Wednesday, November 08, 2006 5:29 AM
To: Stefan Grosse
Cc: r-help@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 [EMAIL PROTECTED] 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,
_
Get FREE company branded e-mail accounts and business Web site from
Microsoft Office Live
__
R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read
Re: [R] CPU or memory
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[EMAIL PROTECTED] 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 [EMAIL PROTECTED] 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 1 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: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Prof Brian Ripley
Sent: Wednesday, November 08, 2006 5:29 AM
To: Stefan Grosse
Cc: r-help@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
Re: [R] CPU or memory
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[EMAIL PROTECTED] 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 [EMAIL PROTECTED] 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 1 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: [EMAIL PROTECTED]
[mailto:[EMAIL PROTECTED] On Behalf Of Prof Brian
Ripley
Sent: Wednesday, November 08, 2006 5:29 AM
To: Stefan Grosse
Cc: r-help@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
Re: [R] CPU or memory
*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 [EMAIL PROTECTED] 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, _ Get FREE company branded e-mail accounts and business Web site from Microsoft Office Live __ R-help@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:[EMAIL PROTECTED] mailto:[EMAIL PROTECTED] [[alternative HTML version deleted]] __ R-help@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.
Re: [R] CPU or memory
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. I think your best option, by far, is to answer the question on your own. Put R and your programs on a USB drive, go to a computer shop, and ask the sales person to let you try a few configurations. Run your simulations, time the results and compare. Keep in mind that the numbers may be affected by the bus and memory frequency (and perhaps memory size/fragmentation). With regards to single/dual core and 32/64 bit, search the archives and the documentation, it was asked before. (I guess dual core and 64 bit would be a sound choice.) One other thing you need to consider (if you haven't already) is ?Rprof, maybe you can significantly improve the efficiency of your code or write parts of it in C or Fortran. -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of John C Frain Sent: Tuesday, November 07, 2006 2:24 PM To: Taka Matzmoto Cc: r-help@stat.math.ethz.ch Subject: Re: [R] CPU or memory *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 [EMAIL PROTECTED] 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, _ Get FREE company branded e-mail accounts and business Web site from Microsoft Office Live __ R-help@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:[EMAIL PROTECTED] mailto:[EMAIL PROTECTED] [[alternative HTML version deleted]] __ R-help@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@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] CPU or memory
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, _ Get FREE company branded e-mail accounts and business Web site from Microsoft Office Live __ R-help@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.
Re: [R] CPU or memory
Taka Matzmoto 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? If your computations consume just a few Mb, it won't make it faster, if it consumes a lot of memory, you will prevent swapping and make it much faster. Uwe Ligges Taka, _ Get FREE company branded e-mail accounts and business Web site from Microsoft Office Live __ R-help@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@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.
