[R] Powerful PC to run R

[Duncan Murdoch]

On 15/05/2011 3:02 PM, Aram Fingal wrote:
>
> On May 13, 2011, at 6:38 AM, Michael Haenlein wrote:
>
>> Dear all,
>>
>> I'm currently running R on my laptop -- a Lenovo Thinkpad X201 (Intel Core
>> i7 CPU, M620, 2.67 Ghz, 8 GB RAM). The problem is that some of my
>> calculations run for several days sometimes even weeks (mainly simulations
>> over a large parameter space). Depending on the external conditions, my
>> laptop sometimes shuts down due to overheating.
>
>
> You didn't mention whether you are using a 64-bit OS or not.  A single 32-bit process can not use more than 2 GB RAM.  If your calculations would benefit from the full 8 GB RAM on your machine, you need to be able to run 64-bit R.   My understanding is that, on Windows, you either have to install the OS as 32-bit and use all 32-bit software or install 64-bit Windows and run all 64-bit software.  A Mac can run 32-bit and 64-bit software simultaneously and I'm not sure about Linux.  In the case of Linux, it probably doesn't matter so much because most Linux software is available as open source and you can compile it yourself either way.

No, 64 bit Windows can run either 32 or 64 bit Windows programs.
>
>>
>> I'm now thinking about buying a more powerful desktop PC or laptop. Can
>> anybody advise me on the best configuration to run R as fast as possible? I
>> will use this PC exclusively for R so any other factors are of limited
>> importance.
>
> You need to evaluate whether RAM or raw processor speed is most critical for what you're doing.  In my case, I upgraded my Mac Pro to 16 GB RAM and was able to do hierarchical clustering heatmaps overnight which previously took more than a week to compute.  Using the Activity Monitor utility, it looks like some of the, even larger, heatmap computations would benefit from 32 GB RAM or more.
>
> Linux runs on the widest range of hardware and that allows you the greatest ability to shop around.  If RAM is the deciding factor, then you can look around for a machine which can hold as much RAM as possible.  If processor speed is the factor, then you can optimize for that.  Windows runs on a reasonable array of hardware but has the disadvantage that the OS, itself, uses a lot of resources.
>
> The Mac has the advantage of flexibility.  When you download the precompiled R package, it comes with both a 32-bit and a 64-bit executable. This is because 32-bit processes run a little faster if you don't need large amounts of RAM.  If you do need the RAM, then you run the 64-bit version.
>

The same is true for Windows binaries on CRAN.

Duncan Murdoch