[FEA]: Update the memory module to use __dealloc__.

[Andy-Jost]

Is this a duplicate?

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Area

cuda.core

Is your feature request related to a problem? Please describe.

I would like abnormal process shutdown to complete gracefully. When testing memory IPC, it was observed that a killed child process sometimes appears to invoke Buffer.__del__ after the CUDA context has been destroyed (see additional context section for error message). This has been observed to result in hard errors including floating point exceptions and segmentation violations.

Describe the solution you'd like

Update Buffer.__del__ (and similar methods) to use Buffer.__dealloc__.

Describe alternatives you've considered

Solutions based on sys.is_finalizing appear to be unreliable.

Additional context

The following messages were output from a killed child process while running cuda_core/tests/memory_ipc tests:

	/opt/hostedtoolcache/Python/3.12.11/x64/lib/python3.12/site-packages/_pytest/unraisableexception.py:67: PytestUnraisableExceptionWarning: Exception ignored in: 'cuda.core.experimental._memory.Buffer.__del__' 
	
	Traceback (most recent call last): 
	File "/opt/hostedtoolcache/Python/3.12.11/x64/lib/python3.12/site-packages/cuda/core/experimental/_device.py", line 991, in __new__ 
	devices = _tls.devices 
	^^^^^^^^^^^^ 
	AttributeError: '_thread._local' object has no attribute 'devices' 
	
	During handling of the above exception, another exception occurred: 
	
	Traceback (most recent call last): 
	File "cuda/core/experimental/_memory.pyx", line 82, in cuda.core.experimental._memory.Buffer._shutdown_safe_close 
	self._mr.deallocate(self._ptr, self._size, stream) 
	File "cuda/core/experimental/_memory.pyx", line 801, in cuda.core.experimental._memory.DeviceMemoryResource.deallocate 
	raise_if_driver_error(err) 
	File "cuda/core/experimental/_utils/cuda_utils.pyx", line 69, in cuda.core.experimental._utils.cuda_utils._check_driver_error 
	raise CUDAError(f"{name}: {expl}") 
cuda.core.experimental._utils.cuda_utils.CUDAError: CUDA_ERROR_INVALID_CONTEXT: This most frequently indicates that there is no context bound to the current thread. This can also be returned if the context passed to an API call is not a valid handle (such as a context that has had ::cuCtxDestroy() invoked on it). This can also be returned if a user mixes different API versions (i.e. 3010 context with 3020 API calls). See ::cuCtxGetApiVersion() for more details. This can also be returned if the green context passed to an API call was not converted to a ::CUcontext using ::cuCtxFromGreenCtx API.

[leofang]

Blocked by #1041.

[cpcloud]

How do we know that implementing __dealloc__ fixes the problem?

it was observed that a killed child process sometimes appears to invoke Buffer.del after the CUDA context has been destroyed

Since __dealloc__ (corresponding to the C API's tp_dealloc slot) is always called after __del__ (if it's defined), it would continue to be invoked after the CUDA context has been destroyed.

So, how does __dealloc__ address the problem?

[cpcloud]

Additionally, the Cython documentation for __dealloc__ explicitly states:

In particular, don’t call any other methods of the object or do anything which might cause the object to be resurrected.

(The bolding is mine)