Install Caffe on EC2

digits_ec2.sh

git clone https://github.com/NVIDIA/DIGITS.git digits
git checkout digits-4.0
cd digits
sudo apt-get install graphviz gunicorn
for req in $(cat requirements.txt); do sudo pip install $req; done

# to run
./digits-devserver -p PORT
# default port is 5000

EC2 Caffe

# ssh into the machine
ssh -i key.pem ubuntu@<ip>

# update the machine
sudo apt-get update && sudo apt-get upgrade -y

# essentials
sudo apt-get install build-essential git htop

# download and extract cuda
wget http://developer.download.nvidia.com/compute/cuda/7.5/Prod/local_installers/cuda_7.5.18_linux.run
chmox +x cuda_7.5.18_linux.run
mkdir nvidia_installers
./cuda_7.5.18_linux.run -extract=`pwd`/nvidia_installers

#############################
# installing nvidia drivers #
#############################

# update kernel to be compatible
sudo apt-get install linux-image-extra-virtual

# disable nouveau
sudo vi /etc/modprobe.d/blacklist-nouveau.conf
blacklist nouveau
blacklist lbm-nouveau
options nouveau modeset=0
alias nouveau off
alias lbm-nouveau off

# then execute
echo options nouveau modeset=0 | sudo tee -a /etc/modprobe.d/nouveau-kms.conf
sudo update-initramfs -u
sudo reboot

# after reboot
sudo apt-get install linux-source
sudo apt-get install linux-headers-`uname -r`

# download and install the drivers
cd nvidia_drivers
wget http://us.download.nvidia.com/XFree86/Linux-x86_64/361.45.11/NVIDIA-Linux-x86_64-361.45.11.run
sudo /bin/bash ./NVIDIA-Linux-x86_64-361.45.11.run 
sudo reboot

# test nvidia drivers
nvidia-smi

##########################
# Install Cuda and cuDNN #
##########################

sudo modprobe nvidia

cd nvidia_installers
sudo ./cuda-linux64-rel-7.5.18-19867135.run
# install the samples in home directory
sudo ./cuda-samples-linux-7.5.18-19867135.run
# to change sample permissions from root to ubuntu
sudo chown -R ubuntu:ubuntu cuda_samples/

# add paths to bashrc
vim ~/.bashrc
export PATH=$PATH:/usr/local/cuda-7.5/bin
export LD_LIBRARY_PATH=:/usr/local/cuda-7.5/lib64
source ~/.bashrc
sudo ldconfig

# install cuDNN
# download cuDNN locally and then use scp
scp -i key.pem cudnn-7.5-linux-x64-v5.1.tgz ubuntu@<ip>:~/nvidia_installers
tar -zxf cudnn-7.5-linux-x64-v5.1.tgz 
cd cuda
sudo cp lib64/* /usr/local/cuda-7.5/lib64/
sudo cp include/cudnn.h /usr/local/cuda/include/

####################
# Installing Caffe #
####################

# install dependencies
sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev protobuf-compiler gfortran libjpeg62 libfreeimage-dev libatlas-base-dev git python-dev python-pip libgoogle-glog-dev libbz2-dev libxml2-dev libxslt-dev libffi-dev libssl-dev libgflags-dev liblmdb-dev python-yaml python-numpy
sudo easy_install pillow

# clone caffe
# git clone https://github.com/BVLC/caffe.git
# git clone https://github.com/NVIDIA/caffe.git
# install python requirements
cd caffe/python
for req in $(cat requirements.txt); do pip install $req; done

# build caffe
cd ~/caffe
cp Makefile.config.example Makefile.config
vim Makefile.config
# Uncomment the line: USE_CUDNN := 1
# Make sure the CUDA_DIR correctly points to our CUDA installation.
make pycaffe -j32
make all -j32
make test -j32

# test caffe
./data/mnist/get_mnist.sh
./examples/mnist/create_mnist.sh
./examples/mnist/train_lenet.sh

echo -e "\nexport CAFFE_HOME=/home/ubuntu/caffe" >> ~/.bashrc