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/ok to test |
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leofang
reviewed
Feb 13, 2026
Comment on lines
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| elif isinstance(ptr, (_driver["CUdeviceptr"])): | ||
| self._cptr = <void*><void_ptr>int(ptr) |
| cdef void * _helper_input_void_ptr(ptr, _HelperInputVoidPtrStruct *buffer) | ||
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| cdef inline void * _helper_input_void_ptr_free(_HelperInputVoidPtrStruct *helper): | ||
| if helper[0]._pybuffer.buf != NULL: |
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Q: Should we check first if helper is NULL?
| self._cptr = NULL | ||
| elif isinstance(ptr, (int)): | ||
| # Easy run, user gave us an already configured void** address | ||
| try: |
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It seems we can avoid code duplication by replacing the try-except block with a call to the new helper like this?
self._cptr = _helper_input_void_ptr(ptr, <_HelperInputVoidPtrStruct*><PyObject*>self)(I'm not so sure about the self casting, I think it's correct because they share the same layout.)
leofang
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We currently accept an
int,CUdeviceptr, or a buffer-providing object as convertible to avoid *. This is currently handled with a class_HelperInputVoidPtr, which mainly exists to manage the lifetime when the input exposes a buffer.This object (like all PyObjects) is allocated on the heap and gets free'd implicitly by Cython at the end of the function. Since it only exists to manage lifetimes when the object exposes a buffer, we pay this heap allocation penalty even in the common case where the input is a simple integer.
This changes the code to statically allocate the
Py_bufferon the stack, and so is faster for similar reasons to #1545. This means we are trading some stack space (88 bytes) for speed. But given that CUDA Python API calls can't recursively call themselves, I'm not concerned.This improves the overhead time in the benchmark in #659 from 2.97us/call to 2.67us/call.
The old
_HelperInputVoidPtrclass stays around here because it is still useful when the input is a list ofvoid *-convertible things and we can't statically determine how much space to allocate.