WIP: CUDA performances

[albop]

Currently, the experiments with CUDA yield terrible performances on AWS/g2.
It may be because, calculations are made on 64 bits by default.
To do :

• test 32 bits calculations
• test 64 bits on a card which supports it natively (e.g. gtx titan)
• try guvectorize(...target='gpu')

[tilman-g]

Dear albop,
I started using the interpolation package and I am amazed by the speed-up of jitting. I would like to explore the GPU-side a bit more as I would be happy to speed things up a bit more and contribute code. Has there been any attempts so far to re-activate the cuda code and if so, what is the current status?

[albop]

No, I did not attempt to reactivate the code, mostly for lack of time and other distractions. One idea would be to tweak a bit the output of codegen. From this discussion, https://groups.google.com/a/continuum.io/forum/#!msg/numba-users/8Hn6GagrXXU/ivQa4JUzCgAJ , I gather there is nothing fundamentally wrong with this approach.
The other idea, would be to test, whether the current eval_linear function can be called on the gpu inside a cuda kernel. This is not totally impossible and would simplify things a lot. Can you try it ?

[tilman-g]

Okay, that makes sense. I am a new to GPU coding, but would really like to try. So I will look into it the next few weeks and see what I can do. I will focus on the eval_linear function for the moment.