-----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
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