Optimize GPU code

[bentsherman]

The matrix library has basic GPU capabilities in that it can use CUBLAS and CUSOLVER in place of CBLAS and LAPACKE when a GPU is available, but I don't think these libraries provide enough on their own to obtain maximum performance with a GPU. There are still a few operations that haven't been implemented with BLAS / LAPACKE, so unless I can figure out a way to do so, the matrix library has to keep host and device memory in sync at all times, which hinders performance. I think there are a few things that can be done to maximize performance:

• Implement custom CUDA kernels for operations which cannot be done entirely with BLAS / LAPACKE. That way, all internal memory transfers can be removed from the matrix library and delegated to the user, based on when data needs to be printed or saved, etc.
• Use CUDA streams for CUBLAS, CUSOLVER, and all memory transfers and custom kernels. Especially once all intermediate operations can be done on the GPU, using streams should increase GPU bandwidth.