├── README.md
└── setup-aws-tensorflow.bash
/README.md:
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1 | # Setting up TensorFlow 0.9 with Python 3.5 on AWS GPU-instance
2 |
3 | ## Description
4 |
5 | `setup-aws-tensorflow.bash` installs the following things on the ec2 `g2.2xlarge` instance running Ubuntu 14.04:
6 |
7 | - Required linux packages
8 | - CUDA 7.5
9 | - cuDNN v4
10 | - Anaconda with Python 3.5
11 | - TensorFlow 0.9
12 | - GPU usage tool `gpustat`
13 |
14 | It is based on the blog post: .
15 |
16 | ## Usage
17 |
18 | Just run `setup_aws_tensorflow.bash` on the aws instance:
19 |
20 | ```bash
21 | ./setup_aws_tensorflow.bash
22 | ```
23 |
24 |
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/setup-aws-tensorflow.bash:
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1 | #!/bin/bash
2 |
3 | # stop on error
4 | set -e
5 | ############################################
6 | # install into /mnt/bin
7 | sudo mkdir -p /mnt/bin
8 | sudo chown ubuntu:ubuntu /mnt/bin
9 |
10 | # install the required packages
11 | sudo apt-get update && sudo apt-get -y upgrade
12 | sudo apt-get -y install linux-headers-$(uname -r) linux-image-extra-`uname -r`
13 |
14 | # install cuda
15 | wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/cuda-repo-ubuntu1404_7.5-18_amd64.deb
16 | sudo dpkg -i cuda-repo-ubuntu1404_7.5-18_amd64.deb
17 | rm cuda-repo-ubuntu1404_7.5-18_amd64.deb
18 | sudo apt-get update
19 | sudo apt-get install -y cuda
20 |
21 | # get cudnn
22 | CUDNN_FILE=cudnn-7.0-linux-x64-v4.0-prod.tgz
23 | wget http://developer.download.nvidia.com/compute/redist/cudnn/v4/${CUDNN_FILE}
24 | tar xvzf ${CUDNN_FILE}
25 | rm ${CUDNN_FILE}
26 | sudo cp cuda/include/cudnn.h /usr/local/cuda/include # move library files to /usr/local/cuda
27 | sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
28 | sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
29 | rm -rf cuda
30 |
31 | # set the appropriate library path
32 | echo 'export CUDA_HOME=/usr/local/cuda
33 | export CUDA_ROOT=/usr/local/cuda
34 | export PATH=$PATH:$CUDA_ROOT/bin:$HOME/bin
35 | export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_ROOT/lib64
36 | ' >> ~/.bashrc
37 |
38 | # install anaconda
39 | wget http://repo.continuum.io/archive/Anaconda3-4.0.0-Linux-x86_64.sh
40 | bash Anaconda3-4.0.0-Linux-x86_64.sh -b -p /mnt/bin/anaconda3
41 | rm Anaconda3-4.0.0-Linux-x86_64.sh
42 | echo 'export PATH="/mnt/bin/anaconda3/bin:$PATH"' >> ~/.bashrc
43 |
44 | # install tensorflow
45 | export TF_BINARY_URL='https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.9.0rc0-cp35-cp35m-linux_x86_64.whl'
46 |
47 | /mnt/bin/anaconda3/bin/pip install $TF_BINARY_URL
48 |
49 | # install monitoring programs
50 | sudo wget https://git.io/gpustat.py -O /usr/local/bin/gpustat
51 | sudo chmod +x /usr/local/bin/gpustat
52 | sudo nvidia-smi daemon
53 | sudo apt-get -y install htop
54 |
55 | # reload .bashrc
56 | exec bash
57 | ############################################
58 | # run the test
59 | # byobu # start byobu + press Ctrl + F2
60 | # htop # run in window 1, press Shift + F2
61 | # watch --color -n1.0 gpustat -cp # run in window 2, press Shift +
62 | # wget https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/models/image/mnist/convolutional.py
63 | # python convolutional.py # run in window 3
64 |
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