tensorflow with gpu 環境配置

一、準備工做

1.1 確保GPU驅動已經安裝

lspci | grep -i nvidia 經過此命令能夠查看GPU信息，測試機已經安裝GPU驅動

nvidia-smi 能夠查看英偉達顯卡信息

1.2 確保gcc安裝

能夠經過gcc -v 查看，若是沒有安裝須要安裝

1.3 確保安裝open-ssh

若是沒有安裝能夠經過 yum install openssh-server 安裝

1.4 確保安裝kernel

 sudo yum install kernel-devel-$(uname -r) kernel-headers-$(uname -r)

二、安裝CUDA工具包

To use TensorFlow with NVIDIA GPUs, the first step is to install the  CUDA Toolkit.

備註：測試機選用的是 CUDA 8.0，不要使用9.x 有坑

三、安裝GPU加速器cuDNN

安裝完CUDA就能夠安裝  cuDNN .

備註：這個地方要選用與CUDA版本匹配的加速器；測試機選用的是： Download cuDNN v6.0 (April 27, 2017), for CUDA 8.0，安裝步驟以下圖所示：

四、安裝或更新pip（若是有須要的話，若是已經有了，能夠選擇性跳過）

TensorFlow itself can be installed using the pip package manager. First, make sure that your system has pip installed and updated:

$ sudo apt-get install python-pip python-dev

$ pip install --upgrade pip

五、安裝TensorFlow

Run the following command to install the TensorFlow Python package using pip:

$ pip install --upgrade tensorflow-gpu

六、測試安裝是否成功

To test the installation, open an interactive Python shell and import the TensorFlow module:

 

(shan) root@ VM-241-228-ubuntu:/data/shan# python

Python 3.5.3 (default, Jun 23 2017, 16:12:41)

[GCC 5.4.0 20160609] on linux

Type "help", "copyright", "credits" or "license" for more information.

>>> import tensorflow as tf

>>> sess = tf.Session()

2017-07-12 19:24:14.030098: I tensorflow/stream_executor/cuda/ cuda_gpu_executor.cc:893] successful NUMA node read from SysFS had negative value (-1), but there must be at least one NUMA node, so returning NUMA node zero

2017-07-12 19:24:14.030833: I tensorflow/core/common_runtime/gpu/ gpu_device.cc:940] Found device 0 with properties:

name: Tesla M40 24GB

major: 5 minor: 2 memoryClockRate (GHz) 1.112

pciBusID 0000:00:06.0

Total memory: 22.40GiB

Free memory: 22.29GiB

2017-07-12 19:24:14.030855: I tensorflow/core/common_runtime/gpu/ gpu_device.cc:961] DMA: 0

2017-07-12 19:24:14.030867: I tensorflow/core/common_runtime/gpu/ gpu_device.cc:971] 0: Y

2017-07-12 19:24:14.030882: I tensorflow/core/common_runtime/gpu/ gpu_device.cc:1030] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla M40 24GB, pci bus id: 0000:00:06.0)

>>> hello_world = tf.constant("Hello, TensorFlow!")

>>> print (sess.run(hello_world))

b'Hello, TensorFlow!'

>>> print (sess.run(tf.constant(123)*tf.constant(456)))

56088

>>>

參考連接

• 官網安裝文檔
• cuDNN 安裝
• CUDA安裝