|| ||Francesc Alted <falted-AT-pytables.org>|
|| ||ANN: Numexpr 1.2 released|
|| ||Wed, 11 Feb 2009 20:33:36 +0100|
Announcing Numexpr 1.2
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.
The main feature added in this version is the support of the Intel VML
library (many thanks to Gregor Thalhammer for his nice work on this!).
In addition, when the VML support is on, several processors can be used
in parallel (see the new `set_vml_num_threads()` function).
When the VML support is on, the computation of transcendental functions
(like trigonometrical, exponential, logarithmic, hyperbolic, power...)
can be accelerated quite a few. Typical speed-ups when using one
single core for contiguous arrays are around 3x, with peaks of 7.5x
(for the pow() function). When using 2 cores the speed-ups are around
4x and 14x respectively.
In case you want to know more in detail what has changed in this
version, have a look at the release notes:
Where I can find Numexpr?
The project is hosted at Google code in:
And you can get the packages from PyPI as well:
How it works?
for a detailed description of the package.
Share your experience
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
Support the Python Software Foundation:
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