[Numpy-discussion] ANN: Numexpr 2.0 released

Francesc Alted faltet@pytables....
Sun Nov 27 07:00:48 CST 2011


========================
 Announcing Numexpr 2.0
========================

Numexpr is a fast numerical expression evaluator for NumPy.  With it,
expressions that operate on arrays (like "3*a+4*b") are accelerated
and use less memory than doing the same calculation in Python.

It wears multi-threaded capabilities, as well as support for Intel's
VML library, which allows for squeezing the last drop of performance
out of your multi-core processors.

What's new
==========

This version comes with support for the new iterator in NumPy
(introduced in NumPy 1.6), allowing for improved performance in
practically all the scenarios (the exception being very small arrays),
and most specially for operations implying broadcasting,
fortran-ordered or non-native byte orderings.

The carefully crafted mix of the new NumPy iterator and direct access
to data buffers turned out to be so powerful and flexible, that the
internal virtual machine has been completely revamped around this
combination.

The drawback is that you will need NumPy >= 1.6 to run numexpr 2.0.
However, NumPy 1.6 has been released more than 6 months ago now, so we
think this is a good time for taking advantage of it.  Many thanks to
Mark Wiebe for such an important contribution!

For some benchmarks on the new virtual machine, see:

http://code.google.com/p/numexpr/wiki/NewVM

Also, Gaëtan de Menten contributed important bug fixes, code cleanup
as well as speed enhancements.  Francesc Alted contributed some fixes,
and added compatibility code with existing applications (PyTables)
too.

In case you want to know more in detail what has changed in this
version, see:

http://code.google.com/p/numexpr/wiki/ReleaseNotes

or have a look at RELEASE_NOTES.txt in the tarball.

Where I can find Numexpr?
=========================

The project is hosted at Google code in:

http://code.google.com/p/numexpr/

You can get the packages from PyPI as well:

http://pypi.python.org/pypi/numexpr

Share your experience
=====================

Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.


Enjoy!

-- 
Francesc Alted


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