[Numpy-discussion] problems building numpy with ACML blas/lapack

Michael Hughes mhughes at cs.brown.edu
Mon Feb 24 14:58:23 EST 2014


I'm trying to build numpy from source to use AMD's ACML for matrix
multiplication (specifically the multi-threaded versions gfortran64_mp).
I'm able to successfully compile and use a working version of np.dot, but
my resulting installation doesn't pass numpy's test suite, instead, I get a
segfault. I'm hoping for some advice on what might be wrong...

 I'm on Debian, with a fresh install of Python-2.7.6. To install numpy,
I've followed exactly the instructions previously posted to this list by
Thomas Unterthiner. See
The only thing I've adjusted is to try to use the gfortran64_mp version of
ACML instead of just gfortran64.

Using those instructions, I can compile numpy-1.8.0 so that it successfully
uses the desired ACML libraries.  I can confirm this by `ldd
site-packages/numpy/core/_dotblas.so`, which shows that I'm linked to
libacml_mp.so as desired. Furthermore, some quick timing tests indicate
that for a 1000x1000 matrix X, calls to np.dot(X,X) have similar speeds as
using custom C code that directly calls the ACML libraries. So, dot seems
to work as desired.

However, when I run numpy.test(verbose=4), I find that I get a seg fault
test_einsum_sums_cfloat128 (test_einsum.TestEinSum) ... Segmentation fault

Any ideas what might be wrong? From my benchmark tests, ACML is way faster
than MKL or other options on my system, so I'd really like to use it, but I
don't trust this current install.

- Mike
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