New gpgpu release! This revision includes, among other things, improvements of the API and the new integration with the ndarray crate.

✨New features

🚩 `integrate-ndarray` feature for integration with `ndarray` crate

Integration with ndarray its been added with #3. I'm no expert using this crate so any comments are welcome!

Upload ndarray arrays to the GPU using GpuArray objects. They save the dimensions of the array previous upload to the GPU.
Take a look at the ndarray example. It has some comments about its usage and problems.

This changes are focused on improve the usability of gpgpu, making more clear the asynchronous intent. The most important changes are:

Background polling: Polling functions cannot be used from gpgpu (can be used from wgpu). They are invoked every 10ms by default.
Read functions: All read function of GpuBuffer and friends have both async and blocking methods:
- read() and read_blocking(): Now it needs into an user provided buffer (#8).
- read_vec() and read_vec_blocking(): Reads into a non-user allocated vector (ol' way).
Write functions: All writes are instantly offloaded, this meaning that writes (updates to GPU) are non-blocking, but it progress cannot be checked.
More clear interaction with wgpu: gpgpu GPU objects can now be created from wgpu ones using from_gpu_parts() and converted back using into_gpu_parts (#5).
Kernel creation is simplified. It now has to be created from a Program which contains information about the shader, entry point and bindings (#4).
Error handling it's been updated. Every GPU object has its own kind of error (#6).

Added CI that checks code format, build status on some platforms and documentation errors. Right now it does not run any example or test (#7).
Docs.rs documentation pulls examples into the usage of some of the functions.
Selection of backend via environment variables is done using Framework::default().
Updated wgpu to 0.12.

Full Changelog: v0.1.0...v0.2.0