recent, I downloaded it a few days
ago).
In your list post you show mkl/10.0.1.014/. I'm using 10.0.3.020,
but I've tried an older 10.0.X version with no better luck. BTW,
my build runs, i.e., I can run some programs that use NumPy.
I have posted to the Intel MKL forum. No responses yet.
-rex
, and if that works, try
the latest MKL (10.0.3.020).
Thanks,
-rex
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Next step is to try icc instead of gcc, and if that works, try
the latest MKL (10.0.3.020).
OK, either I've got a corrupted copy of MKL 10.0.3.020, or it has
a problem. Building with icc MKL 10.0.1.014 works.
Erik, are you reading this? If so, roll back to MKL 10.0.014 and it
should work,
I am trying to build numpy with intel icc and mkl. I don't understand
a lot of what I am doing.
Me, too. I have built it with icc MKL several times in the past,
but cannot build the numpy svn with MKL now. I can build it with
icc and no MKL, and it passes all the tests with no errors.
spectacularly.
-rex
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determined. It just rationalizes hormonal inevitabilities. --Fred Reed
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David wrote:
I have not tried with icc, but the following works for me with the
last mkl (I have only tried numpy).
[mkl]
library_dirs = /home/david/intel/mkl/10.0.1.014/lib/32
lapack_libs = mkl_lapack
mkl_libs = mkl, guide
(of course, adapt the library_dirs accordingly). All test pass. I
David, how do these environment variables compare with yours? Are you sure
MKL is being used?
Adjusted for your local path, what does the ldd command below show?
ldd /usr/local/lib/python2.5/site-packages/numpy/linalg/lapack_lite.so
linux-gate.so.1 = (0xe000)
libmkl_lapack.so =
This is the 3rd time I have reported this problem and a fix.
-rex
- Forwarded message from rex [EMAIL PROTECTED] -
Date: Fri, 9 Nov 2007 11:16:17 -0800
From: rex [EMAIL PROTECTED]
To: Discussion of Numerical Python numpy-discussion@scipy.org
Subject: NumPy 1.04, MKL 10.0, Intel 10.1 icc
that it would help. It did not.
I suggest that efforts to produce a product that ordinary 150
IQ mortals can install rather than add new features would grow the
user population faster. For example, distutils has been broken for
months for Intel MKL. I've posted 3x about it now.
-rex
--
I pray for a soroban
libmkl_vml_def.so
Thanks to all who have helped me with earlier versions.
-rex
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Charles R Harris [EMAIL PROTECTED] [2007-06-24 06:22]:
On 6/23/07, rex [EMAIL PROTECTED] wrote:
Stefan van der Walt [EMAIL PROTECTED] [2007-06-23 15:06]:
On Sat, Jun 23, 2007 at 07:35:35PM +, John Ollinger wrote:
I have just been updating our version of Python, numpy and
scipy
versions of the
software. In particular, ATLAS 3.7.33 does not cause an error.
Is there some reason for you to use such old software? (gcc 3.3.1
kernel 2.4.21)? What platform are you building for?
-rex
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(level=1,verbosity=2)'
[...]
Ran 590 tests in 0.473s
OK
-rex
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David Cournapeau [EMAIL PROTECTED] [2007-06-08 22:49]:
rex wrote:
I don't know if this is the appropriate place for this, but thanks for
any pointers to what the problem is.
-rex
Traceback (most recent call last):
File stdin, line 1, in module
File /usr/lib/python2.5/site
David Cournapeau [EMAIL PROTECTED] [2007-06-09 06:35]:
rex wrote:
I've been using SUSE since version
6.4, and it's always a battle to get Numpy/SciPy running.
This is really Suse fault, honnestly. As Fedora, they have mostly broken
blas or lapack, or at least had for a long time.
Yes
rex [EMAIL PROTECTED] [2007-06-09 11:02]:
I changed the cc_exe line in
numpy-1.0.3/numpy/distutils/intelccompiler.py to:
cc_exe = 'icc -msse3 -xP -fast' #Core 2 Duo
From the numpy-1.03 directory executed:
python setup.py config --compiler=intel build_clib --compiler=intel build_ext
in MoinMoin.)
-rex
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I don't know if this is the appropriate place for this, but thanks for
any pointers to what the problem is.
-rex
deserv:/ # smart install python-numpy
Loading cache...
Updating cache...
## [100%]
Computing
(something like
Scimark, say).
The best compiler flags I've found are: -fast -parallel
In some cases -funroll-loops and -fno-alias helps.
-rex
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http
=100)
LU Mflops: 1010.10(M=1000, N=1000)
-rex
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rex [EMAIL PROTECTED] [2007-04-16 15:53]:
I'm about to build numpy using Intel's MKL 9.1 beta and want to compare
it with the version I built using MKL 8.1. Is the LINPACK
benchmark the most appropriate?
I'm buried in responses. Not.
A well-known benchmark (Scimark?) coded using NumPy/SciPy
took 1.57 seconds
slow (100 iterations) took 154.29 seconds
slow with Psyco (100 iterations) took 119.88 seconds
Python compiled with gcc takes 101 times longer to run this benchmark
than Python/NumPy/icc does.
The C++ version compiled with gcc 4.1.2 runs in .19 seconds.
-rex
--
I liked Occam's
if there are obviously better choices for the Core 2 Duo.
I'd like to run a more comprehensive benchmark, say Scimark translated
from C to Python/NumPy.
http://math.nist.gov/scimark2/download_c.html
-rex
--
Those who forget the pasta are condemed to reheat
David Cournapeau [EMAIL PROTECTED] [2007-01-23 23:40]:
rex wrote:
Robert Kern [EMAIL PROTECTED] [2007-01-23 22:18]:
You need to install the development package for Python. Usually it's named
something like python2.5-devel.
Thank you. Did that, and NumPy compiled with a Brazillion
with an earlier version
as well, thanks to Travis.
-rex
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? I hope I don't have to build Python2.5 from source to build NumPy.
Thanks,
-rex
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is not
being used. I expect a significant speed difference using the Intel
compiler and MKL on a Core 2 Duo.
Why is this so difficult?
Thanks,
-rex
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Has anyone done any benchmarks to compare Numpy's speed with these two
compilers on a Core 2 Duo?
Thanks,
-rex
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