Support new cuFFT callbacks #8242
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cuFFT now supports a new callback mechanism that is not only more performant but also more friendly to dynamic languages like Python and Julia, currently under public preview and will be released in a future CUDA version.
The new approach does not require any ugly compilation of host & device code; instead, we just need to use NVRTC to compile a user-provided device function (currently supporting raw CUDA C++ strings; once we support user-provided types in
@cupyx.jit.rawkernel(#6663) we can also support pure Python functions as device functions) into LTO IR, and pass it to the new cuFFT APIcufftXtSetJITCallbackwhich will be responsible for linking the LTO IR with the cuFFT kernel.The existing callback manager (
_CallbackManager) is renamed to_LegacyCallbackManager, to be distinguished with the new_JITCallbackManager. My suggestion is once this feature is officially released (generally accessible), we add a deprecation warning to_LegacyCallbackManager. Users can currently pick either callback approach via the new optioncp.fft.config.set_cufft_callbacks(..., cb_ver=...).Currently, this feature requires users loading libcufft EA version:
LD_PRELOAD=/path/to/EA/libcufft.so python ..., including running the test suite or sample code, so that the libcufft copy from CUDA Toolkit is not used. I'd like to have this capability included in CuPy sooner, so that users can give it a try and share feedbacks for final adjustment.