Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-24 Thread Nils Wagner
On Thu, 24 Feb 2011 14:26:01 -0500 Frédéric Bastien wrote: > Hi, > > To print the information you can do: > > python -c 'import numpy;numpy.__config__.show()' > > You can access the info directly with: > > numpy.distutils.__config__.blas_opt_info['library_dirs']] > numpy.distutils.__config__

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-24 Thread Frédéric Bastien
Hi, To print the information you can do: python -c 'import numpy;numpy.__config__.show()' You can access the info directly with: numpy.distutils.__config__.blas_opt_info['library_dirs']] numpy.distutils.__config__.blas_opt_info['libraries']] numpy.distutils.__config__.blas_opt_info['include_dir

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-23 Thread Sturla Molden
Den 23.02.2011 18:34, skrev Benjamin Root: > > Just to point out, this person used Matlab 2008. While I do not use > Matlab on a regular basis, I have seen marked improvements in > performance in subsequent versions. They have got a JIT compiler for loops. Matlab is actually an easy language t

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-23 Thread Benjamin Root
On Wed, Feb 23, 2011 at 11:00 AM, Sturla Molden wrote: > Den 23.02.2011 08:32, skrev David: > > This is mostly a test of the blas/lapack used, so it is not very useful > > IMO, except maybe to show that you can deal with non trivial problems on > > top of python (surprisingly, many scientists pro

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-23 Thread Sturla Molden
Den 23.02.2011 08:32, skrev David: > This is mostly a test of the blas/lapack used, so it is not very useful > IMO, except maybe to show that you can deal with non trivial problems on > top of python (surprisingly, many scientists programming a fair bit are > still unaware of the vectorizing concep

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread David
On 02/23/2011 05:45 AM, Sturla Molden wrote: > I came accross some NumPy performance tests by NASA. Comparisons against > pure Python, Matlab, gfortran, Intel Fortran, Intel Fortran with MKL, > and Java. For those that are interested, it is here: This is mostly a test of the blas/lapack used, so i

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Sturla Molden
Den 23.02.2011 00:19, skrev Gökhan Sever: > > I am guessing ATLAS is thread aware since with N=15000 each of the > quad core runs at %100. Probably MKL build doesn't bring much speed > advantage in this computation. Any thoughts? > There are still things like optimal cache use, SIMD extensions,

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Eli Stevens (Gmail)
On Tue, Feb 22, 2011 at 1:48 PM, Gael Varoquaux wrote: > Probably because the numpy binary that the author was using was compiled > without a blas implementation, and just using numpy's internal > lapack_lite. This is a common problem in real life. Is there an easy way to check from within numpy

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Gökhan Sever
On Tue, Feb 22, 2011 at 2:44 PM, Alan G Isaac wrote: > > > I don't believe the matrix multiplication results. > Maybe I misunderstand them ... > > >>> t = timeit.Timer("np.dot(A,B)","import numpy as > np;N=1500;A=np.random.random((N,N));B=np.random.random((N,N))") > >>> print t.timeit(numb

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Gael Varoquaux
On Tue, Feb 22, 2011 at 09:59:26PM +, Pauli Virtanen wrote: > > Probably because the numpy binary that the author was using was compiled > > without a blas implementation, and just using numpy's internal > > lapack_lite. This is a common problem in real life. > It doesn't use blas_lite at the

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Pauli Virtanen
On Tue, 22 Feb 2011 22:48:09 +0100, Gael Varoquaux wrote: [clip] > Probably because the numpy binary that the author was using was compiled > without a blas implementation, and just using numpy's internal > lapack_lite. This is a common problem in real life. It doesn't use blas_lite at the moment.

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Pauli Virtanen
On Tue, 22 Feb 2011 16:44:56 -0500, Alan G Isaac wrote: [clip] > I don't believe the matrix multiplication results. Maybe I misunderstand > them ... > > >>> t = timeit.Timer("np.dot(A,B)","import numpy as > >>> np;N=1500;A=np.random.random((N,N));B=np.random.random((N,N))") > >>> pr

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Gael Varoquaux
On Tue, Feb 22, 2011 at 04:44:56PM -0500, Alan G Isaac wrote: > On 2/22/2011 3:45 PM, Sturla Molden wrote: > > I came accross some NumPy performance tests by NASA. Comparisons against > > pure Python, Matlab, gfortran, Intel Fortran, Intel Fortran with MKL, > > and Java. For those that are interest

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Alan G Isaac
On 2/22/2011 3:45 PM, Sturla Molden wrote: > I came accross some NumPy performance tests by NASA. Comparisons against > pure Python, Matlab, gfortran, Intel Fortran, Intel Fortran with MKL, > and Java. For those that are interested, it is here: > https://modelingguru.nasa.gov/docs/DOC-1762 I don'

Re: [Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Akand Islam
Thanks for posting a nice report. Akand On Tue, Feb 22, 2011 at 2:45 PM, Sturla Molden wrote: > I came accross some NumPy performance tests by NASA. Comparisons against > pure Python, Matlab, gfortran, Intel Fortran, Intel Fortran with MKL, > and Java. For those that are interested, it is here:

[Numpy-discussion] NumPy speed tests by NASA

2011-02-22 Thread Sturla Molden
I came accross some NumPy performance tests by NASA. Comparisons against pure Python, Matlab, gfortran, Intel Fortran, Intel Fortran with MKL, and Java. For those that are interested, it is here: https://modelingguru.nasa.gov/docs/DOC-1762 Sturla ___