On 20/02/14 17:57, Jurgen Van Gael wrote:
Hi All,
I run Mac OS X 10.9.1 and was trying to get OpenBLAS working for numpy.
I've downloaded the OpenBLAS source and compiled it (thanks to Olivier
Grisel).
How?
$ make TARGET=SANDYBRIDGE USE_OPENMP=0 BINARY=64 NOFORTRAN=1
make: *** No targets
On Sat, Feb 22, 2014 at 8:55 PM, Sturla Molden sturla.mol...@gmail.com wrote:
On 20/02/14 17:57, Jurgen Van Gael wrote:
Hi All,
I run Mac OS X 10.9.1 and was trying to get OpenBLAS working for numpy.
I've downloaded the OpenBLAS source and compiled it (thanks to Olivier
Grisel).
How?
$
On 22/02/14 22:00, Robert Kern wrote:
If you actually want some help, you will have to provide a *little* more
detail.
$ git clone https://github.com/xianyi/OpenBLAS
Oops...
$ cd OpenBLAS
did the trick. I need some coffee :)
Sturla
___
On Sat, Feb 22, 2014 at 3:55 PM, Sturla Molden sturla.mol...@gmail.com wrote:
On 20/02/14 17:57, Jurgen Van Gael wrote:
Hi All,
I run Mac OS X 10.9.1 and was trying to get OpenBLAS working for numpy.
I've downloaded the OpenBLAS source and compiled it (thanks to Olivier
Grisel).
How?
$
On 22/02/14 22:15, Nathaniel Smith wrote:
$ make TARGET=SANDYBRIDGE USE_OPENMP=0 BINARY=64 NOFORTRAN=1
You'll definitely want to disable the affinity support too, and
probably memory warmup. And possibly increase the maximum thread
count, unless you'll only use the library on the computer it
On 22/02/14 23:39, Sturla Molden wrote:
Ok, next runner up is Accelerate. Let's see how it compares to OpenBLAS
and MKL on Mavericks.
It seems Accelerate has roughly the same performance as MKL now.
Did the upgrade to Mavericks do this?
These are the compile lines, in case you wonder:
$
First thing I noticed when installing into /opt/OpenBLAS was that the
LAPACK header files were not being copied properly. This was because the
OpenBLAS makefile uses the -D option in the install command which the
default Mac install doesn't support. A quick brew install coreutils
solved that
Indeed I just ran the bench on my Mac and OSX Veclib is more than 2x
faster than OpenBLAS on such squared matrix multiplication (I just
have 2 physical cores on this box).
MKL from Canopy Express is slightly slower OpenBLAS for this GEMM
bench on that box.
I really wonder why Veclib is faster in
Hi All,
I run Mac OS X 10.9.1 and was trying to get OpenBLAS working for numpy.
I've downloaded the OpenBLAS source and compiled it (thanks to Olivier
Grisel). I installed everything to /usr/local/lib (I believe): e.g. ll
/usr/local/lib/ | grep openblas
lrwxr-xr-x 1 37B 10 Feb 14:51
I have exactly the same setup as yours and it links to OpenBLAS
correctly (in a venv as well, installed with python setup.py install).
The only difference is that I installed OpenBLAS in the default
folder: /opt/OpenBLAS (and I reflected that in site.cfg).
When you run otool -L, is it in your
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