Document for device ordinal. (#9398)

- Rewrite GPU demos. notebook is converted to script to avoid committing additional png plots.
- Add GPU demos into the sphinx gallery.
- Add RMM demos into the sphinx gallery.
- Test for firing threads with different device ordinals.

doc/tutorials/param_tuning.rst

@@ -38,10 +38,6 @@ There are in general two ways that you can control overfitting in XGBoost:
   - This includes ``subsample`` and ``colsample_bytree``.
   - You can also reduce stepsize ``eta``. Remember to increase ``num_round`` when you do so.
 
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-Faster training performance
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-There's a parameter called ``tree_method``, set it to ``hist`` or ``gpu_hist`` for faster computation.
 
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 Handle Imbalanced Dataset