Yes, these instructions are no longer valid as there has been some reorganization of the mkl libraries. The path /opt/intel/mkl/10.0.3.020/lib/em64t/ is now /opt/intel/mkl/lib/intel64. Also, the only libraries that need to be included are:
-lmkl_gf_lp64 -lmkl_gnu_thread -lmkl_core The trick to getting rid of the "double complex BLAS" error is to use only the gnu compatible libraries (i.e. use mkl_gnu_thread instead of iomp5). I believe the intel-only libraries use a different convention to pass complex numbers between libraries built with fortran? Thankfully this check detects the error instead of crashing at run time. I used the following to build R-2.14.1 with MKL: export LD_LIBRARY_PATH=/opt/intel/mkl/lib/intel64 ./configure --prefix=/opt/R-2.14.1 --enable-threads=posix --with-lapack --with-blas="-I/opt/intel/mkl/include -L/opt/intel/mkl/lib/intel64 -lmkl_gf_lp64 -lmkl_gnu_thread -lmkl_core -fopenmp -lpthread -lm" Although a highly tuned BLAS may not help much for many applications, I have seen several orders of magnitude performance improvement in some of my work that uses matrix operations heavily and others in my lab have experienced the same. Having R linked against MKL has been HUGELY important for me personally. A custom tuned ATLAS works well too but I find it frustrating that it needs to be re-tuned for each architecture I use (I tend to distribute jobs in a heterogeneous environment). Thanks! Elliott Forney On Fri, Feb 10, 2012 at 8:15 AM, Milan Bouchet-Valat <nalimi...@club.fr> wrote: > Hi! > > I've been playing with MKL for a few days and I noticed the instructions > in the R Installation Administration manual [1] no longer apply. It > seems that since version 10.0 (the one used by the manual), > libmkl_lapack.so has been renamed/split (although the official > explanations seem to imply this was already the case in 10.0 [2]). > > As a consequence, the instructions for dynamic linking no longer work > with the last version (2011-sp1). This is also the case of what is > explained on several sites like [3] or [4]. The manual's instructions to > link statically to MKL still work fine, though. > > I'm merely signaling this fact to more clued people, since I've not been > able to get R to dynamically link to MKL. I'm always getting this notice > during ./configure: >> checking whether double complex BLAS can be used... no > > Anyways, one of the problems is also that it's no longer possible to > make libRblas.so and libRlapack.so symlinks to the Intel libs, as they > are split into several files. > > If nobody knows how or cares about to fix this ATM, a simple warning > that the instructions are outdated would already improve the situation, > as it took me some time to understand things had changed and I wasn't > just being silly. ;-) > > (That said, I'm not convinced using an external BLAS/LAPACK is really > interesting for standard desktops. Performances gains compared to > default packages are incredible in benchmarks, but for real use cases > multi-threading often makes things slower - at least for me, using gnm. > I guess this is mostly interesting for very larges matrices, and not for > many repeated small operations.) > > Regards > > > 1: http://cran.r-project.org/doc/manuals/R-admin.html#MKL > 2: http://software.intel.com/en-us/forums/showthread.php?t=81302 > 3: > http://www.r-bloggers.com/compiling-64-bit-r-2-10-1-with-mkl-in-linux/ > 4: http://www.rd.dnc.ac.jp/~otsu/lecture/RwithMKL.html > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
