Known issues with GPU support.
Only CUDA-enabled NVIDIA GPU hardware is supported
Cloudera Data Science Workbench only supports CUDA-enabled NVIDIA GPU cards.
Heterogeneous GPU hardware is not supported
CDSW nodes that have GPUs must all use the same GPU make and model.
Known Issues with Tensorflow 2.4 and CUDA 11.2
During GPU set up, the dynamic library
libculsolver.so.10 is not read. For more information, see https://github.com/tensorflow/tensorflow/issues/44777.
Workaround: Enter the following commands when starting a session:
!ln -s /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcusolver.so.126.96.36.199 /usr/local/cuda-11.1/targets/x86_64-linux/lib/libcusolver.so.10 !ln -s /usr/lib/x86_64-linux-gnu/libcuda.so.460.73.01 /usr/lib/x86_64-linux-gnu/libcuda.so.1
Multi-Instance GPU (MIG) Support
The NVIDIA Multi-Instance GPU (MIG) feature is not supported.