[copying the list] svd() does support matrices with long vector data. Your example works fine for me on a machine with enough memory with either the reference BLAS/LAPACK or the BLAS/LAPACK used on Fedora 33 (flexiblas backed, I believe, by a version of openBLAS). Take a look at sessionInfo() to see what you are using and consider switching to another BLAS/LAPACK if necessary. Running under gdb may help tracking down where the issue is and reporting it for the BLAS/LAPACK you are using.
Best, luke On Fri, 13 Aug 2021, Dario Strbenac via R-devel wrote:
Good day, I have a real scenario involving 45 million biological cells (samples) and 60 proteins (variables) which leads to a segmentation fault for svd. I thought this might be a good example of why it might benefit from a long vector upgrade. test <- matrix(rnorm(45000000*60), ncol = 60) testSVD <- svd(test) *** caught segfault *** address 0x7fe93514d618, cause 'memory not mapped' Traceback: 1: La.svd(x, nu, nv) 2: svd(test) -------------------------------------- Dario Strbenac University of Sydney Camperdown NSW 2050 Australia ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
-- Luke Tierney Ralph E. Wareham Professor of Mathematical Sciences University of Iowa Phone: 319-335-3386 Department of Statistics and Fax: 319-335-3017 Actuarial Science 241 Schaeffer Hall email: luke-tier...@uiowa.edu Iowa City, IA 52242 WWW: http://www.stat.uiowa.edu ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
