Allow user-provided annotation for kernels generated from `Program` and`ObjectCode`

[leofang]

We have examples like this today

kernel = module.get_kernel("vectorAdd<float>")

which does not tell us what args are expected on the device side, and so when launch(s, config, kernel, ...) is called we cannot do type checking for users.

[leofang]

During the meeting the preliminary idea is to allow users to (optionally) register

• C/C++ types on the device side
• Python types on the host side

similar to what cffi does today, ex:

cuda-python/cuda_core/examples/strided_memory_view_cpu.py

Line 98 in b347255

cpu_prog.cdef(f"{func_sig};")

We still want to be able to keep the fast path that Python int can be interpreted as pointer addresses.

[leofang]

After last November a lot has changed. In particular, as I mentioned in the design meeting yesterday, there is actually a way to retrieve the function signature from CUBINs via driver APIs + CUDA C++ demangler. This is now implemented in cupy/cupy#9801. I hope to reuse/migrate the infrastructure I built there back to cuda-core.