Comments (1)
benvanwerkhoven
commented on June 14, 2024
The Cupy backend also uses NVRTC and through cupy we can avoid having to deal with NVRTC directly, which saves a lot of work. There are some quirks still and the implementation of the cupy backend isn't complete yet, but there is some support already for C++ templated kernels.
In the meantime I'm also working on some code that rewrites a templated CUDA kernel and generates and inserts a wrapper kernel that does have extern "C" linkage. This approach allows templated CUDA kernels to be tuned using the PyCuda backend as a temporary solution. Currently working on this in pull request #116
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Related Issues (20)
- 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
- Special memories only work with PyCUDA backend HOT 9
- Populating pointers of struct from cupy HOT 2
- can we add support for build systems HOT 1
- Some HIP tests need adjustment
- Passing cupy arrays to the compiler backend HOT 1
- Include test code in source distribution to enable testing on conda-forge? HOT 4
- Use the GPU power observer for a Fortran-based program
- API documentation is broken HOT 3
- Adding defines as _additional_ preprocessor definitions HOT 4
- Verification of TunablePrecision parameters only work if using the AccuracyObserver
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