The last time I had this problem i ended up running python in gdb and setting breakpoints at the appropriate dgemm calls. That way i could see exactly what numpy was using to do dgemm. Simon. On Tue, 27 Mar 2007 10:20:41 +1000 "Justin Bedo" <justin.bedo@nicta.com.au> wrote:

Hi All,

I'm trying to compile NumPy using the ATLAS libraries but am having some difficulty with it. I've managed to build numpy such that lapack_lite.so is linked as follows:

linux-gate.so.1 => (0xffffe000) libatlas.so => /usr/local/atlas/lib/libatlas.so (0xb79e9000) libptcblas.so => /usr/local/atlas/lib/libptcblas.so (0xb79c7000) libptf77blas.so => /usr/local/atlas/lib/libptf77blas.so (0xb79ac000) libpython2.5.so.1.0 => /usr/lib/libpython2.5.so.1.0 (0xb788f000) libgfortran.so.1 => /usr/lib/libgfortran.so.1 (0xb7817000) libm.so.6 => /lib/libm.so.6 (0xb77f1000) libgcc_s.so.1 => /lib/libgcc_s.so.1 (0xb77e5000) libc.so.6 => /lib/libc.so.6 (0xb76b7000) libpthread.so.0 => /lib/libpthread.so.0 (0xb769f000) libdl.so.2 => /lib/libdl.so.2 (0xb769a000) libutil.so.1 => /lib/libutil.so.1 (0xb7696000) /lib/ld-linux.so.2 (0x80000000)

However despite this, the performance when multiplying matrices is extremely slow, and only a single thread is used even though lapack_lite.so is linked with the pt atlas libraries. Does anybody know how to fix this problem?

Thanks Justin _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion