[Numpy-discussion] ATLAS problems

[Simon Burton]

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
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