Fabric Engine v1.0 released under AGPL

F

Fabric Paul

Hi everyone - just letting you know that we released v1.0 of Fabric
Engine today. We've open-sourced the core under AGPL, so I hope that
gives you an incentive to get started with high-performance for
Python :)

http://fabricengine.com/technology/benchmarks/ - to give you an idea
of the kind of performance possible. Most of these are with node, but
the core engine is the same - we just bound it to Python.

For those of you using Python on the desktop (particularly if you're
working with 3D), we've started a closed beta on a PyQt framework -
you can see more here: http://fabricengine.com/2012/03/pyqt-framework-for-fabric-engine/
- email (e-mail address removed) if you'd like to take part in the
testing program.

Thanks for your time,

Paul
 
C

Colin J. Williams

Hi everyone - just letting you know that we released v1.0 of Fabric
Engine today. We've open-sourced the core under AGPL, so I hope that
gives you an incentive to get started with high-performance for
Python :)

http://fabricengine.com/technology/benchmarks/ - to give you an idea
of the kind of performance possible. Most of these are with node, but
the core engine is the same - we just bound it to Python.

For those of you using Python on the desktop (particularly if you're
working with 3D), we've started a closed beta on a PyQt framework -
you can see more here: http://fabricengine.com/2012/03/pyqt-framework-for-fabric-engine/
- email (e-mail address removed) if you'd like to take part in the
testing program.

Thanks for your time,

Paul


It seems that sing;e dimension arrays are used in KL. How does this
compare with Numpy?

Colin W.
 
P

Paul Doyle

Hi Colin,

Fabric supports multi-dimensional arrays, and also provides support
for dictionaries. You can read more here:
http://documentation.fabric-engine.com/latest/FabricEngine-KLProgrammingGuide.html

In terms of comparison to Numpy - I'm not familiar with that product,
but some surface level similarities/differences:

- we don't provide high-level functions for scientific computing. This
is something we're looking at now.
- both products provide methods for including existing libraries
(http://documentation.fabric-engine.com/latest/FabricEngine-
ExtensionsReference.html)
- Fabric is a high-performance framework -
http://documentation.fabric-engine.com/latest/FabricEngine-Overview.html
- we haven't benchmarked against R, MatLab etc but we run at the same
speed as multi-threaded compiled code (since that's essentially what
we're doing).

Hope that helps,

Paul
 

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