søn, 13 02 2011 kl. 14:40 -0500, skrev Nir Krakauer: > I found that the regress function runs out of memory when given > moderately large problems, such as > > y = randn(1E5, 1); > X = randn(1E5, 2); > [b, bint, r, rint, stats] = regress(y, X); > > This is because a large (1E5*1E5) intermediate matrix is computed. > Slight modification of the code, as given below, avoids such > computations and enables problems in this size range to be solved > quickly.
Thanks for looking into this. Could you send a diff with your changes as that makes it easier to inspect the changes you suggest? Thanks Søren ------------------------------------------------------------------------------ The ultimate all-in-one performance toolkit: Intel(R) Parallel Studio XE: Pinpoint memory and threading errors before they happen. Find and fix more than 250 security defects in the development cycle. Locate bottlenecks in serial and parallel code that limit performance. http://p.sf.net/sfu/intel-dev2devfeb _______________________________________________ Octave-dev mailing list Octave-dev@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/octave-dev
