This is the numpy I got from pip install (since our spartan test cannot be
run on some machines due to the difference of system numpy version). The
version I install is 1.8, and I found that most of the tests run faster
except the matrix multiply test. I have tested both versions (1.7.1 and
1.8) in serialization and find that they generate the same amount of data
using cPickle.dumps. Therefore, it may be the computation that slows down.
After trying to figure out the slow down reason, I have found this is due
to the atlas and lapack library. When I uses my numpy version, I have
install some other libatlas and liblapack package instead of atlas-base and
lapack package from ubuntu. This is the reason why computation slows down.
When I delete these packages and try to copy these ubuntu packages from
machines that contain these packages, I find it run much faster. Therefore,
I remove the baseline for numpy1.8.


2014-03-17 13:02 GMT-04:00 Russell Power <notifications@github.com>:

> In tests/test_performance.py:
>
> > @@ -20,12 +20,20 @@ class TestPerformance(test_common.ClusterTest):
> >    ''' Test the performance of some applications make sure the changes don't slow down spartan'''
> >
> >    #base line for some applications. The base line cames from the test on 4 machines.
> > -  _base_line = {
> > -                "linear_reg" : 13,
> > -                "matrix_mult" : 14,
> > -                "kmeans" : 16.7,
> > -                "pagerank" : 13
> > -                }
> > +  if np.__version__ < 1.8:
>
> What is this test for? Where do we have a different version of Numpy? Can
> we add a comment for what's going on? It's strange that newer Numpy is
> faster for most things except 3.5 times slower for matmul...
>
> --
> Reply to this email directly or view it on GitHub<https://github.com/spartan-array/spartan/pull/87/files#r10666339>
> .
>



-- 
Chen Qi
Department of Computer Science
School of EECS
Peking University