[R] Linux Standalone Server Suggestions for R

[Campbell]

I think I remember reading somewhere that using Sun Studio compiler
generates binaries that run faster than those built using GCC. 
Presumably this performance gain is increased if the Sun Fortran 95
compiler is used.

Whether the substantial cost of Sun Studio is money better spent than
that on extra RAM or bigger processors is not something I can answer.

HTH

Phineas

>>> "Pikounis, Bill [CNTUS]" <BPikouni at cntus.jnj.com> 09/01/05 10:18 PM
>>>
Jia-Shing,
I missed your original message, but would like to reiterate Bogdan's
comments and suggestions.

In a former life, a colleague of mine led the way for us to construct a
"small farm" of Opteron servers that all had 2 AMD64 CPU's, SUSE
Enterprise
Server OS, and the ability to have up to 16GB RAM. We experimented with
clustering them but that was not successful, and for practical purposes,
not
necessary. Penguin computing (http://www.penguincomputing.com) provided
us
very reliable products, solutions, and service, and I am sure there are
other vendors just as capable. As Bogdan mentioned, search the r-help
archives for various discussions on this over the past few years.

With $50K US, you likely will come up more computing power than you can
dream of (for now at least :-). That can get you multiple 16GB 2CPU
machines, I believe.

Good luck!

Hope that helps,
Bill

-------------------------------
Bill Pikounis, PhD
Nonclinical Statistics
Centocor, Inc.

> -----Original Message-----
> From: bogdan romocea [mailto:br44114 at gmail.com]
> Sent: Thursday, September 01, 2005 2:54 PM
> To: jiso at ucsd.edu
> Cc: R-help at stat.math.ethz.ch
> Subject: Re: [R] Linux Standalone Server Suggestions for R
> 
> 
> Most powerful in what way? Quite a lot depends on the jobs 
> you're going to run.
> 	- To run CPU-bound jobs, more CPUs is better. (Even 
> though R doesn't
> do threading, you can manually split some CPU-bound jobs in several
> parts and run them simultaneously.) Apart from multiple CPUs and
> hyperthreading, check the new dual-core CPUs.
> 	- To run very large jobs, more memory is better. You 
> can easily spend
> most of your money on memory. Get the fastest one.
> 	- You should get 64-bit CPUs, otherwise you won't be 
> able to run very
> large jobs (search the list for details).
> 
> I would suggest that you buy a configuration that can handle more CPUs
> and memory than you think you need now (say, at least 4 max CPUs and
> 16 GB max memory), then keep on adding more memory and CPUs as your
> needs change.
> hth,
> b.
> 
> 
> > -----Original Message-----
> > From: Jia-Shing So [mailto:jiso at ucsd.edu] 
> > Sent: Wednesday, August 31, 2005 10:03 PM
> > To: r-help at stat.math.ethz.ch
> > Cc: Phuoc Hong
> > Subject: [R] Linux Standalone Server Suggestions for R
> > 
> > 
> > Hi All,
> > 
> > My group is  looking for any suggestions on what to purchase to  
> > achieve the most powerful number crunching system that $50k 
> > can buy.   
> > The main application that will be used is R so input on what 
> > hardware  
> > benefits R most will be appreciated.  The requirements are 
> > that it be  
> > a single standalone server (i.e. not a cluster solution), and 
> > it that  
> > must be able to run unix/linux.  If anyone has any experience/ 
> > suggestions regarding the following questions that would also be  
> > greatly appreciated.
> > 
> > AMD vs Intel chips, especially 64-bit versions of the two?
> > Using Itanium/Opterons and if so how much of a performance 
> boost did  
> > you achieve vs other 64-bit chip sets?
> > Also, does anyone know if there is an upper thresh hold on much  
> > memory R can use?
> > 
> > Thanks in advance for any help and suggestions,
> > 
> > Jia-Shing So
> > Programmer Analyst
> > Biostatistics and Bioinformatics Lab
> > University of California, San Diego
> > 
> > ______________________________________________
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