I just want to point this out because I feel like there's a good chance a lot of people won't have gotten this far:
Because our implementation does not explicitly depend on Python we are able to overcome many of the shortcomings of the Python runtime such as running without the GIL and utilising real threads to dispatch custom Numba kernels running at near C speed without the performance limitations of Python.
Yes, using Numba we can just-in-time compile numeric Python logic straight down to machine code, so naturally we can achieve some pretty impressive numbers on kernel execution.
In case many people didn't reach the bottom here are the links to the repo and the docs. The project is still in early stages, but is public and released under a BSD license.
Comments
I just want to point this out because I feel like there's a good chance a lot of people won't have gotten this far:
Because our implementation does not explicitly depend on Python we are able to overcome many of the shortcomings of the Python runtime such as running without the GIL and utilising real threads to dispatch custom Numba kernels running at near C speed without the performance limitations of Python.
Yes, using Numba we can just-in-time compile numeric Python logic straight down to machine code, so naturally we can achieve some pretty impressive numbers on kernel execution.
In case many people didn't reach the bottom here are the links to the repo and the docs. The project is still in early stages, but is public and released under a BSD license.
* http://blaze.pydata.org/docs/
* https://github.com/ContinuumIO/blaze