Hi, I'm following up to a post I made to r-help here: http://r.789695.n4.nabble.com/Trouble-configuring-R-to-use-ACML-tt2337193.html#a2337193 I have verified that LD_LIBRARY_PATH is set... I set it in /etc/bash.bashrc (is that ok?) and it shows up when I echo $LD_LIBRARY_PATH I also tried adding the paths to the ld.so cache as Prof Ripley had suggested. I get the same results when running configure. So after that I decided to try and replace libRblas.so with a link to libacml_mp.so. I ran a regular configure command followed by a make, then added the link. I now have this in my R lib folder... lrwxrwxrwx 1 root root 46 2010-08-25 09:20 libRblas.so -> /opt/acml4.4.0/gfortran64_mp/lib/libacml_mp.so* Is there any way I can verify that it is using this libacml_mp library now? I ran a test script and R still only shows 100% cpu use, as if it's not using multiple processors/cores. Is there a specific sample script I could run that should use more than 100% so I can verify whether this is working or not? Or maybe a command that will tell me which BLAS R is using? Thanks in advance. -- View this message in context: http://r.789695.n4.nabble.com/Trying-to-configure-R-to-use-acml-mp-tp2338257p2338257.html Sent from the R devel mailing list archive at Nabble.com.
Ok, I have verified that ACML appears to be working because when I run set.seed (1) m <- 10000 n <- 5000 A <- matrix (runif (m*n),m,n) system.time (B <- crossprod(A)) It multi threads properly. My initial test script doesn't seem to utilize multiple cores, I am going to paste it below if anyone has any insight as to why R can't multithread this particular operation. It seems it might just be a code optimization problem on our end, at least I know that R is configured to use multiple cores when it can now. Y <- rnorm(1e5) X <- matrix(as.factor(rep(1:1e2, 5e3)), 1e5, 10) system.time(fit <- lm(Y~X[,1] + X[,2] + X[,3] + X[,4] + X[,5])) Thanks -- View this message in context: http://r.789695.n4.nabble.com/Trying-to-configure-R-to-use-acml-mp-tp2338257p2338482.html Sent from the R devel mailing list archive at Nabble.com.