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Special memories only work with PyCUDA backend #210
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I do know that constant memory works with the CuPy backend. But now that the number of backends is expanding, a table with feature completeness per backend would be nice to have. In the meantime, I was also inspecting the code and I think you're onto something interesting here. There is some very old code in core.py that I've quoted below. This indeed includes the if's for The code in kernel_tuner/kernel_tuner/core.py Lines 497 to 516 in b3ff4cd
are actually not used at all and could be removed. |
I've just made some extensions to the documentation on backends see pull request #213 |
It would appear that run_kernel maybe does use these methods. Will look into this soon. |
I will fix this tomorrow. And base my "patch" on the mega pull-request from @fjwillemsen (unless that is merged into master already today or tomorrow). |
Perfect, then I will just fix this issue on master after your merge, and avoid the conflicts :) |
Great, I will do this today. Will reach to you if something is not clear about the new development environment. |
Minor set of fixes, addressing mainly Issue #210
This should be fixed for now. |
The functions:
copy_shared_memory_args
copy_constant_memory_args
copy_texture_memory_args
In
core.py
check ifself.lang == "CUDA"
, and not work with e.g. CuPy or other backends that implement the functionality.Moreover, this is only checked if using
run_kernel
and nottune_kernel
. I am waiting for some comments before fixing it, as I may have overlooked something.The text was updated successfully, but these errors were encountered: