This introduces new functions:
```
// returns kernel(args...) running on the CPU.
Eigen::run_on_cpu(Kernel kernel, Args&&... args);
// returns kernel(args...) running on the GPU.
Eigen::run_on_gpu(Kernel kernel, Args&&... args);
Eigen::run_on_gpu_with_hint(size_t buffer_capacity_hint, Kernel kernel, Args&&... args);
// returns kernel(args...) running on the GPU if using
// a GPU compiler, or CPU otherwise.
Eigen::run(Kernel kernel, Args&&... args);
Eigen::run_with_hint(size_t buffer_capacity_hint, Kernel kernel, Args&&... args);
```
Running on the GPU is accomplished by:
- Serializing the kernel inputs on the CPU
- Transferring the inputs to the GPU
- Passing the kernel and serialized inputs to a GPU kernel
- Deserializing the inputs on the GPU
- Running `kernel(inputs...)` on the GPU
- Serializing all output parameters and the return value
- Transferring the serialized outputs back to the CPU
- Deserializing the outputs and return value on the CPU
- Returning the deserialized return value
All inputs must be serializable (currently POD types, `Eigen::Matrix`
and `Eigen::Array`). The kernel must also be POD (though usually
contains no actual data).
Tested on CUDA 9.1, 10.2, 11.3, with g++-6, g++-8, g++-10 respectively.
This MR depends on !622, !623, !624.
