Setup for deep learning workstation

This page covers the steps for setting up a machine primarily intended for deep learning analyses. This is assuming Ubuntu has already been installed.

Ubuntu installation notes:

Other tips/notes on running analyses: KerasTips

Initial setup

Early on, presumably right after installation of OS, remember to update all packages:

sudo apt-get update
sudo apt-get upgrade

Package installation

These two are definite necessities. In particular, need to install openssh-server before basically anything else because otherwise we can't get SSH access.

sudo apt-get openssh-server
sudo apt-get install tightvncserver

The following may not be necessary anymore -- it was for our old VNC setup. But it shouldn't hurt to install these packages anyway, just in case we want to use something like the old setup again.

sudo apt-get install ubuntu-desktop gnome-panel gnome-settings-daemon metacity nautilus gnome-terminal

OLD VNC server configuration

 #!/bin/sh
[-x /etc/vnc/startup] && exec /etc/vnc/startup
[ -r $HOME/.Xresources ] && xrdb $HOME/.Xresources
xsetroot -solid grey
vncconfig -iconic & x-terminal-emulator -geometry 80x24+10+10 -ls -title "$VNCDESKTOP Desktop" & x-window-manager & gnome-panel & gnome-settings-daemon & metacity & nautilus

NEW VNC server configuration

Steps roughly follow https://www.digitalocean.com/community/tutorials/how-to-install-and-configure-vnc-on-ubuntu-16-04. Exact instructions below:

Install the following packages:

sudo apt-get install xfce4 xfce4-goodies
sudo apt-get install autocutsel

Next, start up VNC:

vncserver:yourvncnumber

It will prompt you to set and confirm a password; do so. Then end the session:

vncserver -kill :yourvncnumber

This creates ~/.vnc/xstartup.

Either edit ~/.vnc/xstartup , or delete it and make a new file. IF MAKING A NEW FILE, enter this command as well:

chmod 755 ~/.vnc/xstartup

The new contents of ~/.vnc/xstartup should be:

 #!/bin/bash
xrdb $HOME/.Xresources
startxfce4 &

After you've edited (or deleted/recreated) xstartup, start a new VNC desktop:

vncserver :yourvncnumber -geometry 1280x800

When you open the VNC viewer, you might get a "Welcome to first start" message; select "Use default config". (You may also get an error message saying Ubuntu had a problem but it doesn't appear to cause issues.)

That should be the basic VNC setup. Other convenience functions/packages/etc below:

Adding users

sudo adduser newusername
sudo usermod -aG sudo newusername

Install additional packages

Enable copy/paste on VNC

Allows copy/paste between VNC windows and your computer. This has to be done at the beginning of every VNC session (so you should only need to do it once, unless you kill your VNC session, Agnew/Calculon/etc restart, etc).

run autocutsel -fork

Enable the Tab key https://www.starnet.com/xwin32kb/tab-key-not-working-when-using-xfce-desktop/





Keras setup

Install and run Anaconda

First, download the Anaconda installer from their website. (Just Google it.) We want Linux version, x86, 64-bit, Python 3.6 edition. Then:

sudo bash [name of anaconda .sh installer file]
when prompted, install into: /opt/anaconda3

Next, do the CUDA setup:

Download CUDA installer from NVidia (or actually, just get from Agnew/Calculon/etc.) For reference, the version we're running on Agnew/Calculon/Lrrr/Ndnd as of June 2017 is 8.0.44. Before we can actually install it though, we need to follow the following pages' instructions for shutting down display manager and blacklisting Nouveau. The links follow immediately, but see below them for the short summary of what we actually have to do.

http://askubuntu.com/questions/788323/change-runlevel-on-16-04

http://askubuntu.com/questions/481414/install-nvidia-driver-instead-nouveau (top solution)

(First askubuntu page:) To disable starting up in graphical mode:

sudo systemctl isolate multi-user.target
sudo systemctl enable multi-user.target
sudo systemctl set-default multi-user.target

(Second askubuntu page:) Now keep nouveau from running by editing the blacklist:

sudo nano /etc/modprobe.d/blacklist.conf

Add the following lines to that blacklist file (see Agnew/Calculon's blacklist files if you want to confirm you got it right)

blacklist amd76x_edac #this might not be required for x86 32 bit users.
blacklist vga16fb
blacklist nouveau
blacklist rivafb
blacklist nvidiafb
blacklist rivatv

Now the following is probably not necessary (as there shouldn't be any proprietary Nvidia drivers on the system yet) but not a bad idea to run anyway:

sudo apt-get remove --purge nvidia*

Now, restart the system. When restarted, you should be able to run the CUDA installer.

Running the CUDA installer

In most cases, you can just run the cuda_8.0.44_linux.run (or whatever version) installer file and accept most of the defaults. However, note the following exception:

GTX 1080Ti GPU (current as of June 2017 None of the CUDA installers currently have the right drivers for this card. So when you install CUDA, do not let it install the GPU driver! Instead, do everything else normally but don't install any driver. Then download the current driver for a 1080Ti card from the Nvidia website. (Lrrr is using NVIDIA-Linux-x86_64-381.22.run as of June 2017.) Install the driver -- if it says there is already a driver installed (e.g., maybe from a past failed CUDA installation attempt or something), and asks to overwrite the old driver, allow it to overwrite! Otherwise, CUDA installation and everything following it should be the same as written below.

Detour over; back to CUDA installation. When asked if you want to install samples, say yes and put them in /opt/cuda_samples.

CUDA should now be installed. Next up is CUDNN -- need to download that from Nvidia developer program or just get from Agnew/Calculon/etc.

Unzip/untar/whatever the CUDNN files e.g. cudnn-8.0-linux-x64-v5.1.tar. Should yield a cuda directory with lib64 and include subdirectories. Copy the files in each of those to the corresponding /usr/local/cuda subdirectories (will require sudo), e.g. sudo cp lib64/* /usr/local/cuda/lib64/ (assuming you are in the cuda directory already).

Now we need to put CUDA in the path and set up its environment variable(s) -- should just need to add the following to each user's .bashrc file (and exit shell / re-enter shell to take effect):

export PATH="/usr/local/cuda/bin:$PATH"
export set CUDA_ROOT=/usr/local/cuda

Also, it seems you need to enter sudo ldconfig /usr/local/cuda/lib64 at some point after installing all this stuff -- we think this has to do with making the system aware of the shared libraries? Seems like we need to enter it periodically but it's not clear when -- maybe after each restart???

below still needs revising

sudo /opt/anaconda3/bin/pip install theano==0.9.0
sudo /opt/anaconda3/bin/pip install keras==1.2
apt-get install git

(We're installing old versions of Theano and Keras for now -- just to make life easier.)

Edit keras.json (in home folder)

Change backend: from tensorflow -> theano

Change image_dim_ordering: from tf -> th

Make .theanorc in home directory

Mount Farnsworth

Only needs to be done once. Will only unmount if we do so explicitly or if Agnew/Calculon/Lrrr/Ndnd gets rebooted (or if their network connection dies)

Install cifs-utils package: sudo apt-get install cifs-utils sudo mkdir /mnt/eeg_data_analysis (or whatever the share is named)

sudo mount -t cifs -o username=matt //farnsworth/eeg_data/analysis /mnt/eeg_data_analysis/ (replace username with your Farnsworth username)

Start VNC session

Enter in Terminal:

ssh yourusername@agnew/calculon.local
vncserver :yourvncnumber -geometry  (whatever, e.g.) 1280x800

Enter in VNC:

agnew/calculon.local :yourvncnumber

End VNC session

vncserver -kill :yourvncnumber