alteryx / alteryx/evalml

Add support for GPU acceleration

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needs design new feature
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Python
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Description

In the usability blitz, @christopherbunn showed [what looked like an 8x speedup in wall-clock runtime](https://alteryx.quip.com/gwW9AQg5m0Nq/Evalml-Usability-Blitz-April-2020#PFNACAoq60N) when GPU support was enabled in our catboost component. So yes, GPUs are awesome :)

It appears [sklearn has chosen not to prioritize GPU support](https://alteryx.quip.com/gwW9AQg5m0Nq/Evalml-Usability-Blitz-April-2020#PFNACAoq60N). However, [xgboost](https://xgboost.readthedocs.io/en/latest/gpu/), [lightgbm](https://lightgbm.readthedocs.io/en/latest/GPU-Tutorial.html) and [catboost](https://catboost.ai/docs/features/training-on-gpu.html) support GPU acceleration.

Proposed plan:
* Update catboost and xgboost components and pipelines to support turning on GPU acceleration as a boolean flag in the init, default false
* Once the automl strategy project #272 is in, we could write a GPU-specific automl strategy which only runs the pipelines which support GPU acceleration, with it enabled
* That means this is blocked on #272

Questions to consider:
* Should we find more GPU-enabled algorithms?
* Does this vary from platform to platform? We could choose to support only on linux initially.

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