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Update GPU doc. (#4953)

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This commit is contained in:
Jiaming Yuan
2019-10-16 05:54:09 -04:00
committed by GitHub
parent 7e72a12871
commit 185e3f1916
2 changed files with 17 additions and 8 deletions
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15
doc/gpu/index.rst
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@@ -46,6 +46,8 @@ Supported parameters
+--------------------------------+--------------+
| ``max_bin`` | |tick| |
+--------------------------------+--------------+
| ``gamma`` | |tick| |
+--------------------------------+--------------+
| ``gpu_id`` | |tick| |
+--------------------------------+--------------+
| ``n_gpus`` (deprecated) | |tick| |
@@ -75,9 +77,13 @@ The GPU algorithms currently work with CLI, Python and R packages. See :doc:`/bu
:caption: Python example
param['gpu_id'] = 0
param['max_bin'] = 16
param['tree_method'] = 'gpu_hist'
.. code-block:: python
:caption: With Scikit-Learn interface
XGBRegressor(tree_method='gpu_hist', gpu_id=0)
Single Node Multi-GPU
=====================
@@ -85,9 +91,10 @@ Single Node Multi-GPU
Multi-node Multi-GPU Training
=============================
XGBoost supports fully distributed GPU training using `Dask
<https://dask.org/>`_. See Python documentation :ref:`dask_api` and worked examples `here
<https://github.com/dmlc/xgboost/tree/master/demo/dask>`_.
XGBoost supports fully distributed GPU training using `Dask <https://dask.org/>`_. For
getting started see our tutorial :doc:`/tutorials/dask` and worked examples `here
<https://github.com/dmlc/xgboost/tree/master/demo/dask>`_, also Python documentation
:ref:`dask_api` for complete reference.
Objective functions