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Add CUDA_VISIBLE_DEVICES warning explanation so it can be avoided
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docs/cub/benchmarking.rst

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@@ -174,6 +174,10 @@ Therefore, it's critical that you run it in a clean build directory without any
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Running cmake is enough. Alternatively, you can also clean your build directory with.
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Furthermore, the tuning scripts require some additional python dependencies, which you have to install.
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To select the appropriate CUDA GPU, first identify the GPU ID by running `nvidia-smi`, then set the
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desired GPU using `export CUDA_VISIBLE_DEVICES=x`, where `x` is the ID of the GPU you want to use (e.g., `1`).
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This ensures your application uses only the specified GPU.
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.. code-block:: bash
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ninja clean

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