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Tensorflow on CentOS7 w/ Nvidia GPUs

First boot up a GPU instance. (ami-31490d51)
CentOS 7, amazon style (whatever that means).

sudo yum -y update  
sudo yum install -y kernel-devel kernel-headers gcc make  
sudo yum install -y epel-release  
sudo yum install -y --enablerepo=epel dkms  
sudo reboot

This updates your yum repos, then installs a bunch of kernel-ness.

At this point, the installed kernel may not be the same as the running kernel. (Bummer, man.)

To ensure consistency, we also reboot.

Compare your running kernel with the installed source:
uname -r  
rpm -q kernel-devel

If they match, you're good!

Locally,
scp ~/.boto ec2-user@$(cat IP)

Then: 

aws s3 cp s3://val314159-gpu/install-files . --recursive  

sudo sh NVIDIA-Linux-x86_64-367.35.run

answer all the legalese...
(you don't need the 32-bit version)

nvidia-smi

[ec2-user@ip-172-31-3-130 ~]$ nvidia-smi 
Sun Jul 17 20:30:06 2016  
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 367.35                 Driver Version: 367.35                    |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GRID K520           Off  | 0000:00:03.0     Off |                  N/A |
| N/A   32C    P0     1W / 125W |      0MiB /  4036MiB |      0%      Default |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                       GPU Memory |
|  GPU       PID  Type  Process name                               Usage      |
|=============================================================================|
|  No running processes found                                                 |
+-----------------------------------------------------------------------------+
[ec2-user@ip-172-31-3-130 ~]$

sudo sh cuda7.5.18linux.run

45 spaces accept y y y y RET y y RET

wget https://doc-00-6s-docs.googleusercontent.com/docs/securesc/rmchn5rrn9h0vrd4d7vnrua4a8oqe4bc/nqmk91e589k17pa0vl52hcvpubdc2o88/1468728000000/13951467387256278872/09470983940600970531/0Bz7KyqmuGsilT0J5dmRCM0ROVHc?e=download&nonce=j3uirr35c8dtk&user=09470983940600970531&hash=1tedlt945gjfq5n8a3m3k5jf6aukktp7

==============

sudo yum -y update  
sudo yum install -y kernel-devel kernel-headers gcc make  
sudo yum install -y epel-release  
sudo yum install -y --enablerepo=epel dkms  
sudo reboot  

   wget https://s3.amazonaws.com/val314159-gpu/install-files/nvidia_cuda_stuff.tar
   tar xvf nvidia_cuda_stuff.tar 
   sudo sh cuda_7.5.18_linux.run 

   export LD_LIBRARY_PATH=/usr/local/cuda/lib64
   export PATH=$PATH:/usr/local/cuda/bin
   sudo sh NVIDIA-Linux-x86_64-367.35.run

   tar xvzf cudnn-7.0-linux-x64-v4.0-prod.tgz 
   sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64/
   sudo cp cuda/include/cudnn.h /usr/local/cuda/include/
   nvidia-smi
   sudo bash -c 'echo export LD_LIBRARY_PATH=/usr/local/cuda/lib64 >>/etc/bashrc'
   sudo bash -c 'echo export PATH=\$PATH:/usr/local/cuda/bin >>/etc/bashrc'

export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.9.0-cp27-none-linux_x86_64.whl  
sudo pip install --upgrade $TF_BINARY_URL  
sudo reboot