[Numpy-discussion] building NumPy with Intel CC & MKL
david at ar.media.kyoto-u.ac.jp
Wed Jan 24 03:15:52 CST 2007
> David Cournapeau <david at ar.media.kyoto-u.ac.jp> [2007-01-23 23:40]:
> But installing software is typically easy for Windows users.
I am not sure installing numpy using MKL library is easier on windows :)
> IMO, the
> difficulty of installing Linux applications is a huge barrier to wider
> adoption of Linux. I started trying Linux in 1994, and stopped using
> Windows entirely in 1999. I'm old (66), and becoming dumber as my brain
> shrinks, but I'm still reasonably sharp (or so I like to think). Over
> the years, NumPy and SciPy have been very difficult to install for me
> using SUSE (the SUSE developers have different ideas of what paths
> should be from most of the rest of the world. If I were King I'd lock
> 'em all in a room and tell them that if they could not agree on a
> directory structure for Linux in 48 hours, they would all be
> killed. Impending death tends to focus attention on the problem.)
> Two of my two closest friends have advanced degrees. One is a PhD in
> orbital mechanics from UCSD, and the other did everything for a PhD in
> computer science but complete his thesis. Both have tried Linux
> repeatedly, but found it to require more effort to install and maintain
> than they are willing to expend. If people of this caliber are repelled
> by Linux, I think developers need to wake up and smell the coffee. When
> people with PhDs in science are turned off by the difficulty the problem
> needs to be addressed.
My parents both have college degree in science, and my mother has a hard
time using the mouse, and she is younger than you :)
You are not trying to install a program, but compiling it with a
specific set of libraries; I don't see how this is difficult than
windows (I would say it is worse because of the lack of decent command
line shell in windows).
About numpy/scipy and linux: installing software on linux is not
difficult; installing software which is not packaged for your
distribution is. Installing from sources is easier on linux than on
windows, in my experience, and building binaries which work on linux
across distributions extremely difficult (and not a fun thing to do).
The real problem of numpy/scipy now is that it is not packaged yet by
all major distributions, but this should change soon.
>>>> import numpy
>>>> print numpy
> <module 'numpy' from '/usr/lib/python2.5/site-packages/numpy/__init__.pyc'>
This means that the numpy you use in python is the system-wide path.
Either this is the numpy installed by RPM, or the one you build yourself
that you overwrote (not something you should do normally).
Assuming a standard set of libraries, one way to build numpy and install
it in your home directory (and as such avoiding messing up with the
system, and you don't need root rights)
- uncompress the numpy tarball and go to the numpy directory
- run "python setup.py build"
- run "python setup.py install --prefix=$HOME/local" to install
everything in a local path.
Now, when you run python, you need to tell him to look for python
modules in your $HOME/local:
or PYTHONPATH=$HOME/local/lib/python2.5/site-packages/ python
Depending on your python version (which you can check with python -V)
This is not different on linux than on windows, by the way :)
> What am I to make of this? Is it the rpm numpy or is it the numpy I
> built using the Intel compiler and MKL?
> Thanks for the reply, but I'm still confused.
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