Difference between revisions of "NautilusServer"

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     echo export PATH=$ANACONDA_PATH/bin:\$PATH >> ~/.bashrc
 
     echo export PATH=$ANACONDA_PATH/bin:\$PATH >> ~/.bashrc
  
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=== Install tensorflow and keras ===
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 +
These will be installed in a [https://conda.io/docs/intro.html conda] environment called '''deep''':
 +
***************
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 +
    export ENVNAME=deep
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    conda create --name $ENVNAME
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    source activate $ENVNAME
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    conda install theano keras tensorflow tensorflow-gpu opencv pillow spyder matplotlib
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 +
To check Keras is working:
 +
 +
    python -c "from keras.models import Sequential;Sequential()"
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 +
To check the GPU is working with tensorflow:
 +
 +
Check this first:
 +
 +
    nvidia-smi
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 +
It should list two GPUs.
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 +
Then make sure the following script runs and finds one CPU and two GPUS: https://bitbucket.org/damienjadeduff/uhem_keras_tf/src/master/sariyer_python3/test_tf_gpu.py
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 +
Run:
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    python test_tf_gpu.py
  
 
== Server Construction ==
 
== Server Construction ==

Revision as of 18:23, 14 August 2017

Accessing

IP: 160.75.27.83

SSH port: 1542

Access from: ITU or ITU VPN.

VPN Help

SSH help

The SSH command to connect from a Unix environment:

   ssh -X -p 1542 hossein@160.75.27.83

Switch meanings:

  • -p 1542: connect on port 1542
  • -X: This allows you to run X applications. Omit it if you will be pure command line.

Note: to check that X forwarding is working, once you have connected, try running on the server the command:

   xeyes

Or:

   dolphin

You could for example run spyder like this. But there can be some latency across the network.

Setting up a deep learning environment

Install anaconda

   export ANACONDA_PATH_PARENT=$HOME/software
   export ANACONDA_PATH=$ANACONDA_PATH_PARENT/anaconda3
   export ANACONDA_INSTALLER=Anaconda3-4.3.1-Linux-x86_64.sh
   mkdir -p ~/tmp
   cd ~/tmp
   mkdir -p $ANACONDA_PATH_PARENT
   wget https://repo.continuum.io/archive/$ANACONDA_INSTALLER
   sudo bash $ANACONDA_INSTALLER -b -p $ANACONDA_PATH
   export PATH=$ANACONDA_PATH/bin:$PATH
   echo PATH: $PATH
   echo >> ~/.bashrc
   echo export PATH=$ANACONDA_PATH/bin:\$PATH >> ~/.bashrc

Install tensorflow and keras

These will be installed in a conda environment called deep:

   export ENVNAME=deep
   conda create --name $ENVNAME
   source activate $ENVNAME
   conda install theano keras tensorflow tensorflow-gpu opencv pillow spyder matplotlib

To check Keras is working:

   python -c "from keras.models import Sequential;Sequential()"

To check the GPU is working with tensorflow:

Check this first:

   nvidia-smi

It should list two GPUs.

Then make sure the following script runs and finds one CPU and two GPUS: https://bitbucket.org/damienjadeduff/uhem_keras_tf/src/master/sariyer_python3/test_tf_gpu.py

Run:

   python test_tf_gpu.py

Server Construction

Software

OS

Kubuntu 16.04.3 LTS

Graphics Drivers

Nvidia 384.59 drivers installed using runfile NVIDIA-Linux-x86_64-384.59.run

Installed using (to keep using the integrated graphics as main display graphics):

   sudo ./NVIDIA-Linux-x86_64-370.28.run --no-opengl-files --no-x-check --disable-nouveau


CUDA Drivers

Installed using

   cuda_8.0.61.2_linux.run