Hi, We are gradually moving most of climate data and model output analyses to R. We have a 2 x Core 2 Duo Mac with 9GB memory and 3TB disk space, i.e. ideal for such work... Question: Does the standard (binary distribution) of R use all of the cores and access all of the available memory? Or does one have to recompile R to take advantages of more powerful hardware available around? N?zhet Dalfes ITU -------------- next part -------------- A non-text attachment was scrubbed... Name: dalfes.vcf Type: text/x-vcard Size: 421 bytes Desc: not available Url : https://stat.ethz.ch/pipermail/r-sig-mac/attachments/20071011/15db5db8/attachment.vcf
R and multicore architectures?
3 messages · Nüzhet Dalfes, Sean Davis, Simon Urbanek
N?zhet Dalfes wrote:
Hi, We are gradually moving most of climate data and model output analyses to R. We have a 2 x Core 2 Duo Mac with 9GB memory and 3TB disk space, i.e. ideal for such work... Question: Does the standard (binary distribution) of R use all of the cores and access all of the available memory? Or does one have to recompile R to take advantages of more powerful hardware available around?
R will use the available memory, but keep in mind that MacOS is still a 32-bit operating system, so 9 Gb of RAM won't be used, I don't think. R will use only one processor unless you write code specifically using mechanisms like Rmpi OR if you simply run multiple R processes simultaneously. Recompiling will not change that. Sean
On Oct 11, 2007, at 7:38 AM, N?zhet Dalfes wrote:
We are gradually moving most of climate data and model output analyses to R. We have a 2 x Core 2 Duo Mac with 9GB memory and 3TB disk space, i.e. ideal for such work... Question: Does the standard (binary distribution) of R use all of the cores and access all of the available memory?
The CRAN binary is a 32-bit build, so it will use only up to 4GB of RAM per process. An unofficial 64-bit binary of R is available from the R for Mac developer page, but CRAN doesn't provide binary packages for that build. However, the CRAN build supports vecLib, and as such it will use all four cores for matrix operations that are supported by LAPACK.
Or does one have to recompile R to take advantages of more powerful hardware available around?
You don't have to, but you can compile 64-bit version of R if you need more RAM in one R process (you can still use all 9GB of RAM when using parallel R processes, c.f. snow). In Tiger the 64-bit version of R is somewhat limited compared to the 32-bit version, because most system libraries are not available in 64-bit, however Leopard supports full 64-bit build including the GUI. We will release a corresponding binary in due course. Cheers, Simon