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Fix specifying gpu_id, add tests. (#3851)

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* Rewrite gpu_id related code.

* Remove normalised/unnormalised operatios.
* Address difference between `Index' and `Device ID'.
* Modify doc for `gpu_id'.
* Better LOG for GPUSet.
* Check specified n_gpus.
* Remove inappropriate `device_idx' term.
* Clarify GpuIdType and size_t.
This commit is contained in:
Jiaming Yuan
2018-11-06 18:17:53 +13:00
committed by GitHub
parent 1698fe64bb
commit f1275f52c1
20 changed files with 341 additions and 203 deletions
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doc/gpu/index.rst
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@@ -63,7 +63,7 @@ GPU accelerated prediction is enabled by default for the above mentioned ``tree_
The device ordinal can be selected using the ``gpu_id`` parameter, which defaults to 0.
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 gpu device order is ``mod(gpu_id + i) % n_visible_devices`` for ``i=0`` to ``n_gpus-1``. 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.
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