diff --git a/doc/getstarted/build_and_install/docker_install.rst b/doc/getstarted/build_and_install/docker_install.rst
index e95de35f4da35fee511551f13bc6026532cce5c3..88d83573044f5e36eb656292394565a0682b8cbe 100644
--- a/doc/getstarted/build_and_install/docker_install.rst
+++ b/doc/getstarted/build_and_install/docker_install.rst
@@ -56,25 +56,38 @@ The PaddlePaddle images don't contain any entry command. You need to write your
Download and Run Docker images
------------------------------
-You have to install Docker in your machine which has linux kernel version 3.10+ first. You can refer to the official guide https://docs.docker.com/engine/installation/ for further information.
+Currently, Docker is supported on macOS, Windows and Linux distributions. Please check out `Install Docker Engine `_ to find out much more details.
-You can use :code:`docker pull ` to download images first, or just launch a container with :code:`docker run` \:
+PaddlePaddle on CPU
+.....................
-.. code-block:: bash
+You can use :code:`docker pull ` to download images, or directly launch a container with :code:`docker run` \:
- docker run -it paddledev/paddle:cpu-latest
+ .. code-block:: bash
+ docker run -it paddledev/paddle:cpu-latest
-If you want to launch container with GPU support, you need to set some environment variables at the same time:
+PaddlePaddle on GPU
+.....................
-.. code-block:: bash
+To build GPU version, you will need the following installed:
+
+ .. code-block:: bash
+
+ 1. a CUDA-capable GPU
+ 2. NVIDIA CUDA Toolkit (available at http://developer.nvidia.com/cuda-downloads)
+
+
+Then, you will need to mount related CUDA driver and library into container.
+
+ .. code-block:: bash
- export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
- export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
- docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest
+ export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
+ export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
+ docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest
-Some notes for docker
+Some notes for Docker
---------------------
Performance
diff --git a/doc_cn/build_and_install/install/docker_install.rst b/doc_cn/build_and_install/install/docker_install.rst
index 40339659be406ec72da8ad89b6d5dd38d72bb5ae..90a5c937094164985a4f23ac8ce1de2577042afb 100644
--- a/doc_cn/build_and_install/install/docker_install.rst
+++ b/doc_cn/build_and_install/install/docker_install.rst
@@ -60,21 +60,38 @@ mac osx或者是windows机器，请参考
`mac osx的安装文档 `_ 和
`windows 的安装文档 `_ 。
+
+启动CPU版Docker镜像
+...................
+
您可以使用 :code:`docker pull` 命令预先下载镜像，也可以直接执行
:code:`docker run` 命令运行镜像。执行方法如下:
-.. code-block:: bash
+ .. code-block:: bash
+
+ $ docker run -it paddledev/paddlepaddle:cpu-latest
+
+即可启动和进入PaddlePaddle的container。
+
+启动GPU版Docker镜像
+...................
+
+首先, 请参考以下链接，在机器上安装CUDA Toolkit。
+
+ .. code-block:: bash
- $ docker run -it paddledev/paddle:cpu-latest
+ NVIDIA CUDA Toolkit (available at http://developer.nvidia.com/cuda-downloads)
-即可启动和进入PaddlePaddle的container。如果运行GPU版本的PaddlePaddle，则需要先将
-cuda相关的Driver和设备映射进container中，脚本类似于
+其次，需要将cuda相关的驱动和设备映射进container中，脚本类似于
-.. code-block:: bash
+ .. code-block:: bash
+
+ $ export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
+ $ export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
+ $ docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddlepaddle:latest-gpu
- $ export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
- $ export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
- $ docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddle:gpu-latest
+使用PaddlePaddle
+..................
进入Docker container后，运行 :code:`paddle version` 即可打印出PaddlePaddle的版本和构建
信息。安装完成的PaddlePaddle主体包括三个部分， :code:`paddle` 脚本， python的
diff --git a/doc_cn/faq/index.rst b/doc_cn/faq/index.rst
index 551430eb41765673700b7c6568e4b483641f2cac..838fa651d852ed04a18081413d8bb5e27b9d04b3 100644
--- a/doc_cn/faq/index.rst
+++ b/doc_cn/faq/index.rst
@@ -202,3 +202,18 @@ PaddlePaddle的参数使用名字 :code:`name` 作为参数的ID，相同名字
解决办法是：
* 卸载PaddlePaddle包 :code:`pip uninstall paddle`, 清理掉老旧的PaddlePaddle安装包，使得单元测试有一个干净的环境。如果PaddlePaddle包已经在python的site-packages里面，单元测试会引用site-packages里面的python包，而不是源码目录里 :code:`/python` 目录下的python包。同时，即便设置 :code:`PYTHONPATH` 到 :code:`/python` 也没用，因为python的搜索路径是优先已经安装的python包。
+
+
+9. 运行Docker GPU镜像出现 "CUDA driver version is insufficient"
+----------------------------------------------------------------
+
+用户在使用PaddlePaddle GPU的Docker镜像的时候，常常出现 `Cuda Error: CUDA driver version is insufficient for CUDA runtime version`, 原因在于没有把机器上CUDA相关的驱动和库映射到容器内部。
+具体的解决方法是：
+
+.. code-block:: bash
+
+ $ export CUDA_SO="$(\ls usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
+ $ export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
+ $ docker run ${CUDA_SO} ${DEVICES} -it paddledev/paddlepaddle:latest-gpu
+
+更多关于Docker的安装与使用, 请参考 `PaddlePaddle Docker 文档 `_ 。