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Deprecate single node multi-gpu mode (#4579)

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* deprecate multi-gpu training

* add single node

* add warning
This commit is contained in:
Rong Ou
2019-06-18 20:51:38 -07:00
committed by Rory Mitchell
parent 6757654337
commit e94f85f0e4
5 changed files with 16 additions and 6 deletions
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4
doc/build.rst
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@@ -196,9 +196,9 @@ From the command line on Linux starting from the XGBoost directory:
cmake .. -DUSE_CUDA=ON
make -j4
.. note:: Enabling multi-GPU training
.. note:: Enabling distributed GPU training
By default, multi-GPU training is disabled and only a single GPU will be used. To enable multi-GPU training, set the option ``USE_NCCL=ON``. Multi-GPU training depends on NCCL2, available at `this link <https://developer.nvidia.com/nccl>`_. Since NCCL2 is only available for Linux machines, **multi-GPU training is available only for Linux**.
By default, distributed GPU training is disabled and only a single GPU will be used. To enable distributed GPU training, set the option ``USE_NCCL=ON``. Distributed GPU training depends on NCCL2, available at `this link <https://developer.nvidia.com/nccl>`_. Since NCCL2 is only available for Linux machines, **distributed GPU training is available only for Linux**.
.. code-block:: bash

2
doc/gpu/index.rst
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@@ -80,6 +80,8 @@ The GPU algorithms currently work with CLI, Python and R packages. See :doc:`/bu
Single Node Multi-GPU
=====================
.. note:: Single node multi-GPU training is deprecated. Please use distributed GPU training with one process per GPU.
Multiple GPUs can be used with the ``gpu_hist`` tree method using the ``n_gpus`` parameter. which defaults to 1. If this is set to -1 all available GPUs will be used. If ``gpu_id`` is specified as non-zero, the selected gpu devices will be from ``gpu_id`` to ``gpu_id+n_gpus``, please note that ``gpu_id+n_gpus`` must be less than or equal to the number of available GPUs on your system. As with GPU vs. CPU, multi-GPU will not always be faster than a single GPU due to PCI bus bandwidth that can limit performance.
.. note:: Enabling multi-GPU training