Installing Jupiter on Amazon EC2
##I - Anaconda install on EC2 (ubuntu instance)
cd ~
wget https://repo.continuum.io/archive/Anaconda3-4.2.0-Linux-x86_64.sh
bash Anaconda3-4.2.0-Linux-x86_64.sh -b
echo 'PATH="/home/ubuntu/anaconda3/bin:$PATH"' >> .bashrc
source ~/.bashrc
##II - jupyter setup
conda update jupyter
jupyter notebook --generate-config
key=$(python -c "from notebook.auth import passwd; print(passwd())")
cd ~
mkdir certs
cd certs
certdir=$(pwd)
openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout my.key -out my.pem
cd ~
sed -i "1 a\
config = get_config()\\
config.NotebookApp.certfile = u'$certdir/my.pem'\\
config.NotebookApp.keyfile = u'$certdir/my.key'\\
config.NotebookApp.ip = '*'\\
config.NotebookApp.open_browser = False\\
config.NotebookApp.password = u'$key'\\
config.NotebookApp.port = 8889" .jupyter/jupyter_notebook_config.py
##III - Launch jupyter
cd ~
mkdir notebook_root
cd notebook_root
jupyter notebook
The following things are installed:
Essentials
Cuda Toolkit 7.0
cuDNN Toolkit 6.5
Bazel 0.1.4 (Java 8 is a dependency)
TensorFlow 0.6
After launching your instance g2.2xlarge using the Ubuntu Server 14, install the essentials :
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install -y build-essential git python-pip libfreetype6-dev libxft-dev libncurses-dev libopenblas-dev gfortran python-matplotlib libblas-dev liblapack-dev libatlas-base-dev python-dev python-pydot linux-headers-generic linux-image-extra-virtual unzip python-numpy swig python-pandas python-sklearn unzip wget pkg-config zip g++ zlib1g-dev
sudo pip install -U pip
TensorFlow requires installing CUDA Toolkit 7.0. To do this, run:
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1410/x86_64/cuda-repo-ubuntu1410_7.0-28_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1410_7.0-28_amd64.deb
rm cuda-repo-ubuntu1410_7.0-28_amd64.deb
sudo apt-get update
sudo apt-get install -y cuda
sudo apt-get install make
sudo apt-get update
sudo apt-get install gcc
sudo apt-get install g++
sudo apt-get install git
git clone --recursive https://github.com/dmlc/xgboost
cd xgboost; cp make/config.mk ./config.mk; make -j4
cd python3-package
sudo python3 setup.py install
conda install libgcc
wget https://bootstrap.pypa.io/ez_setup.py -O - | sudo python
To make an EBS volume available for use on Linux
- Connect to your instance using SSH. For more information, see Step 2: Connect to Your Instance.
- Use the lsblk command to view your available disk devices and their mount points (if applicable) to help you determine the correct device name to use.
[ec2-user ~]$ lsblk
NAME MAJ:MIN RM SIZE RO TYPE MOUNTPOINT
xvdf 202:80 0 100G 0 disk
xvda1 202:1 0 8G 0 disk /
The output of lsblk removes the /dev/ prefix from full device paths. In this example, /dev/xvda1 is mounted as the root device (note the MOUNTPOINT is listed as /, the root of the Linux file system hierarchy), and /dev/xvdf is attached, but it has not been mounted yet. 3. Determine whether you need to create a file system on the volume. Use the sudo file -s device command to list special information, such as file system type. ''' sudo mount /dev/xvdb ./notebook_root/ sudo cp /etc/fstab /etc/fstab.orig vi /etc/fstab sudo vi /etc/fstab cd notebook_root/ pwd sudo vi /etc/fstab df '''