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

[Michael Hughes]

Hello,

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
http://numpy-discussion.10968.n7.nabble.com/numpy-ACML-support-is-kind-of-broken-td35454.html.
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.

Thanks!
- Mike
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