Error handling in CUDA extensions within the MoonEP library, specifically the premature termination of Python processes due to uncatchable CUDA errors.

## Problem

The CUDA extension's `CUCHECK` and `CUDACHECK` macros print an error and call
`exit(EXIT_FAILURE)`. Any checked CUDA driver or runtime failure therefore
terminates the Python process from inside the library.

```text
Python caller --> pybind binding --> CUDA error --> exit()
|
`--> process ends
```

The caller cannot catch the error, attach operation context, clean up its own
state, or coordinate an orderly distributed shutdown.

## Reproduction

Pass `nvl_multicast_import` a valid POSIX file descriptor for `/dev/null`. The
descriptor is valid at the OS boundary but is not a CUDA-exported shareable
allocation, so the CUDA import call returns an error.

On an H100 NVL with `origin/master`, the child process printed the old macro's
CUDA error and exited with status 1. The parent regression failed because no
Python exception was catchable:

```text
assert result.returncode == 0
actual returncode: 1
stderr: Failed: CUDA error ... 'invalid device ordinal'
```

This is a defined error path: it does not fabricate or reinterpret an opaque
CUDA allocation handle.

## Expected behavior

- Checked CUDA calls raise a Python-visible `RuntimeError` through pybind.
- The message identifies the failed expression, symbolic error name, numeric
code, and CUDA description when available.
- Partially acquired VMM resources are released while the C++ stack unwinds.
- Successful allocation, map...