Such a calculation would be dominated by the time spent inside a call to an offf-the-shelf C matrix inversion library used by R and is not really any test of R itself.
On 3/9/07, Richard Morey <[EMAIL PROTECTED]> wrote: > My adviser has a Mac notebook that he bought 6 months ago, and I have a > PC notebook I bought a month ago. Here are the respective specs, as far > as I know them: > > His: > Mac OSX > 1 GB DDR2 RAM > Intel Core Duo, 2 GHz (2MB cache per core) > Unknown HD > > Mine > Windows Vista Home Premium 32bit > 2 GB DDR2 RAM > Intel Core 2 Duo, 2 GHz (4MB cache) > 5400 RPM Hard Drive > > > We are both running R. As a test to see whose laptop was faster, we > decided to invert large random matrices. In R language, it looks like this: > > N=2000 > A=rnorm(N^2) > A=matrix(A,ncol=N) > solve(A) > > This creates a matrix of 4,000,000 random normal deviates and inverts > it. His computer takes about 7 seconds, while mine takes about 14. Why > the difference? I have several working hypotheses, and it would be > interesting to see what you guys think. > > 1. R on Mac was compiled with optimizations for the CPU, with R for > Windows was not. I could test this by compiling R with the Intel > compiler, or GCC with optimizations, and seeing if I get a significant > speed boost. > > 2. His R is 64 bit, while mine is for 32 bit windows. (I'm not sure how > much of a diference that makes, or whether OSX is 64 bit.) > > 3. Data is getting swapped to the hard drive, and my hard drive is > slower than his. I chose a slower hard drive to get bigger capacity for > the price. > > This is not intended to be an OMG MACOS = TEH R0X0R thread. I'm just > trying to explain the discrepency. > > Thanks! > > ______________________________________________ > 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.