Comments (2)
I'm not sure how to do this from cupy, but with pycuda it should be easy. If you have PyCuda device allocation you can just cast it to an int to get the GPU memory address. From a cupy array you may be able to extract the pointer somehow, but I just had a look at cupy and DLpack, but I'm not sure how to extract the device pointer from those data types. If using PyCuda is an option for you, I think you could make it work.
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I haven't used either PyCuda or cupy so happy to use whichever is easier - thanks for the suggestion
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Related Issues (20)
- Versioned documentation HOT 2
- OO interface
- framework_time is growing over time HOT 4
- redesigning the readme HOT 1
- Instance won't be None HOT 2
- Error in expdist.py HOT 2
- C compiler version parsing error HOT 3
- Refactoring cache files HOT 2
- matrix multiplication tutorial in the documentation HOT 1
- [bug] Parameter `objective_higher_is_better` in `tune_kernel` call cannot be manually specified HOT 2
- observer documentation issues
- brute force strategy to respect max_fevals
- How to get the compiled function which can be called later? HOT 3
- `ValueError: name is not a valid identifier: {k}`
- Remove dependence on `OrderedDict`? HOT 4
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- can we add support for build systems HOT 1
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