🐛 Bug
Current CUDA Toolkit version is 11.8, while the CUDA version in the Nvidia driver is 11.4. This is usually not a problem because of Minor Version Compatibility, however Numba in particular doesn't support MVC yet, so the entire CUDA functionality of Numba is not working with the current docker image (it used to work before), producing the error "[222] Call to cuLinkAddData results in UNKNOWN_CUDA_ERROR" known to occur when a mismatch like this happens.
As Numba's CUDA wrapper is sort of the only sensible way of getting custom GPU algorithms to work together with pytorch in Kaggle, this is quite unfortunate.
To Reproduce
- Open any notebook implementing a Numba CUDA kernel, such as this one: https://www.kaggle.com/code/harshwalia/2-custom-cuda-kernels-in-python-with-numba/notebook
- Change the environment in notebook settings from pinned to latest
- Run the kernel (in the above example, the first 3 cells)
Expected behavior
Numba kernels working