[docs] Update GPU documentations

Better description for setting OpenCL platform and GPU IDs in documentations

docs/GPU-Targets.rst

@@ -76,6 +76,9 @@ Using a bad ``gpu_device_id`` is not critical, as it will fallback to:
 However, using a bad combination of ``gpu_platform_id`` and ``gpu_device_id`` will lead to a **crash** (you will lose your entire session content).
 Beware of it.
 
+Your system might have multiple GPUs from different vendors ("platforms") installed. You can use the `clinfo`_ utility to identify the GPUs on each platform. On Ubuntu, you can install ``clinfo`` by executing ``sudo apt-get install clinfo``. On Windows, you can find a list of your OpenCL devices using the utility `GPUCapsViewer`_. If you have a discrete GPU by AMD/NVIDIA and an integrated GPU by Intel, make sure to select the correct ``gpu_platform_id`` to use the discrete GPU.
+
+
 CPU Only Architectures
 ----------------------
 
@@ -286,3 +289,9 @@ Keep in mind that using the integrated graphics card is not directly possible wi
 .. _AMD APP SDK: http://developer.amd.com/amd-accelerated-parallel-processing-app-sdk/
 
 .. _NVIDIA CUDA Toolkit: https://developer.nvidia.com/cuda-downloads
+
+.. _clinfo: https://github.com/Oblomov/clinfo
+
+.. _GPUCapsViewer: http://www.ozone3d.net/gpu_caps_viewer/
+
+

docs/GPU-Tutorial.rst

@@ -126,7 +126,8 @@ Now we create a configuration file for LightGBM by running the following command
     echo "num_threads=$(nproc)" >> lightgbm_gpu.conf
 
 GPU is enabled in the configuration file we just created by setting ``device=gpu``.
-It will use the first GPU installed on the system by default (``gpu_platform_id=0`` and ``gpu_device_id=0``).
+In this configuration we use the first GPU installed on the system (``gpu_platform_id=0`` and ``gpu_device_id=0``). If ``gpu_platform_id`` or ``gpu_device_id`` is not set, the default platform and GPU will be selected.
+You might have multiple platforms (AMD/Intel/NVIDIA) or GPUs. You can use the `clinfo`_ utility to identify the GPUs on each platform. On Ubuntu, you can install ``clinfo`` by executing ``sudo apt-get install clinfo``. If you have a discrete GPU by AMD/NVIDIA and an integrated GPU by Intel, make sure to select the correct ``gpu_platform_id`` to use the discrete GPU.
 
 Run Your First Learning Task on GPU
 -----------------------------------
@@ -196,3 +197,5 @@ Huan Zhang, Si Si and Cho-Jui Hsieh. "`GPU Acceleration for Large-scale Tree Boo
 .. _Python Package Examples: https://github.com/Microsoft/LightGBM/tree/master/examples/python-guide
 
 .. _GPU Acceleration for Large-scale Tree Boosting: https://arxiv.org/abs/1706.08359
+
+.. _clinfo: https://github.com/Oblomov/clinfo

docs/GPU-Windows.rst

@@ -397,8 +397,9 @@ Now that you compiled LightGBM, you try it... and you always see a segmentation
    :align: center
    :target: ./_static/images/screenshot-segmentation-fault.png
 
-Please check you are using the right device and whether it works with the default ``gpu_device_id = 0`` and ``gpu_platform_id = 0``.
-If it still does not work with the default values, then you should follow all the steps below.
+Please check if you are using the right device (``Using GPU device: ...``). You can find a list of your OpenCL devices using `GPUCapsViewer`_, and make sure you are using a discrete (AMD/NVIDIA) GPU if you have both integrated (Intel) and discrete GPUs installed. 
+Also, try to set ``gpu_device_id = 0`` and ``gpu_platform_id = 0`` or ``gpu_device_id = -1`` and ``gpu_platform_id = -1`` to use the first platform and device or the default platform and device.
+If it still does not work, then you should follow all the steps below.
 
 You will have to redo the compilation steps for LightGBM to add debugging mode. This involves:
 
@@ -582,3 +583,6 @@ And open an issue in GitHub `here`_ with that log.
 .. _CMake: https://cmake.org/download/
 
 .. _here: https://github.com/Microsoft/LightGBM/issues
+
+.. _GPUCapsViewer: http://www.ozone3d.net/gpu_caps_viewer/
+