Installing packages

A project log for 32-TFLOP Deep Learning GPU Box

A super-fast linux-based machine with multiple GPUs for training deep neural nets

robotbugsrobotbugs 06/04/2016 at 05:030 Comments

The next tasks were

  1. Ensure all packages up to date with apt-get
  2. Ensure that python3 was ok
  3. Install scipy and any other relevant packages
  4. Install CUDA toolkit 7.5
  5. Install cuDNN
  6. Install pip3 because TensorFlow needs this
  7. Install TensorFlow

I installed scipy using 'sudo apt-get install python3-scipy'.

I installed CUDA toolkit using the deb(network) link, using dpkg, then apt-get.

I then went on to attempt to install cuDNN and chose the newest version (5). This turned out to be a mistake. Also cuDNN installation is confusing. In the end I installed it using the two deb packages, not manually. It puts the header files and shared libraries in the usual place but not the same place as CUDA toolkit.

Then I installed pip3 because this is the only way to get TensorFlow for linux. I followed the instructions on the TensorFlow site for linux with python3 and a GPU and everything built ok.

I needed to set the LD_LIBRARY_PATH to get python3 to find the cuda libraries.

I ran the tests on the TensorFlow page and everything seemed ok. But then when I tried to run the MNIST training example it crashed.

Eventually I found that this crash is because TensorFlow needs cuDNN version 4 not version 5. So now I have to go back and screw with the installation trying to remove cuDNN and install the older one and possibly rebuild TensorFlow.