I'm starting to get a clearer idea of what you mean: there are two (possibly three) routes you can go:
1) If your matrices are sparse (mostly zero) there's some specialized work on multiplying them quickly 2) You can look at the RcppArmadillo package which interfaces to a very high quality linear algebra backend. I think this one is likely to give a very nice speedup without requiring too much additional work. 3) (This one is the most technically difficult, but it can be pretty powerful if done correctly) You can recompile R using a BLAS (basic linear algebra system) that's optimized for your machine, rather than a rather generic one that most computers come with. Something like this: http://math-atlas.sourceforge.net/ Michael On Thu, Nov 17, 2011 at 5:51 PM, Sachinthaka Abeywardana <sachin.abeyward...@gmail.com> wrote: > Hi Michael, > Thanks for that. The X1 and X2 are vectors are typically 1000 by 3 matrices, > and hoping to scale up to much larger dimensions (say 20,000 by 3). > I do appreciate your help and seems like this is the best way to do this, I > was just wondering if I could squeeze out just a bit more performance, thats > all. > Anyway thanks again, much appreciated. > Thanks, > Sachin > > On Fri, Nov 18, 2011 at 9:15 AM, R. Michael Weylandt > <michael.weyla...@gmail.com> wrote: >> >> I fail to see why you would need another idea: you asked how to >> multiply matrices efficiently, I told you how to multiply matrices >> efficiently. >> >> if you want to calculate X1-X2 times W times X1-X2, then simply do so: >> >> X1 <- matrix(1:6, 3) >> X2 <- matrix(7:12, 3) >> W = matrix(runif(9), 3) >> >> t(X1-X2) %*% W %*% (X1-X2) >> >> which gives >> >> 142.7789 142.7789 >> 142.7789 142.7789 >> >> You could squeeze out one iota more of speed with >> >> crossprod(X1-X2, W) %*% (X1-X2) >> >> to get the same result, but unless you are doing massive scale linear >> processing, I'm not sure it's worth the loss of clarity. >> >> I was only giving you a heads up on the sometimes confusing difference >> between matrix multiplication in MATLAB and in R by which a vector is >> not a 1d matrix and so does not require explicit transposition. >> >> Michael >> >> >> On Thu, Nov 17, 2011 at 4:35 PM, Sachinthaka Abeywardana >> <sachin.abeyward...@gmail.com> wrote: >> > I'm not quite sure of what you mean by not worry if it's 1d R matrices. >> > X1 >> > and X2 are both n by d matrices and W is d by d. >> > >> > Thanks for the help though. Any other ideas? >> > >> > Thanks >> > Sachin >> > >> > On Friday, November 18, 2011, R. Michael Weylandt >> > <michael.weyla...@gmail.com> wrote: >> >> The fastest is probably to just implement the matrix calculation >> >> directly in R with the %*% operator. >> >> >> >> (X1-X2) %*% W %*% (X1-X2) >> >> >> >> You don't need to worry about the transposing if you are passing R >> >> vectors X1,X2. If they are 1-d matrices, you might need to. >> >> >> >> Michael >> >> >> >> On Thu, Nov 17, 2011 at 1:30 AM, Sachinthaka Abeywardana >> >> <sachin.abeyward...@gmail.com> wrote: >> >>> Hi All, >> >>> >> >>> I am trying to convert the following piece of matlab code to R: >> >>> >> >>> XX1 = sum(w(:,ones(1,N1)).*X1.*X1,1); #square the elements of >> >>> X1, >> >>> weight it and repeat this vector N1 times >> >>> XX2 = sum(w(:,ones(1,N2)).*X2.*X2,1); #square the elements of >> >>> X2, >> >>> weigh and repeat this vector N2 times >> >>> X1X2 = (w(:,ones(1,N1)).*X1)'*X2; #get the weighted >> >>> 'covariance' term >> >>> XX1T = XX1'; #transpose >> >>> z = XX1T(:,ones(1,N2)) + XX2(ones(1,N1),:) - 2*X1X2; #get >> >>> the >> >>> squared weighted distance >> >>> >> >>> which is basically doing: z=(X1-X2)' W (X1-X2) >> >>> >> >>> What would the best way (for SPEED) to do this? or is vectorizing as >> >>> above >> >>> the best? Any hints, suggestions? >> >>> >> >>> Thanks, >> >>> Sachin >> >>> >> >>> [[alternative HTML version deleted]] >> >>> >> >>> ______________________________________________ >> >>> R-help@r-project.org 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@r-project.org 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.
