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Tips and tricks

Local machine

SSH hosts

Adding ssh hosts to your SSH configuration will make working with remote superhosts, hosts, and boards much quicker and easier. After setting them up, you will be able to connect to any machine through a single ssh <machine> command.

To begin, make a ~/.ssh/config file.

touch ~/.ssh/config

Then open that file in a text editor and add a Host entry for each machine that you want to interact with remotely.

Typically machines that you can connect to directly will have a configuration like this:

Host <short name>
  User <username>
  HostName <host name or IP address>

For security, the port on which ssh connections are accepted is often changed. To specify a port, add the following to the Host entry.

Host <short name>
  ...
  Port 1234

Finally, many machines (especially hosts and boards) are not accessible through the open internet and must instead be accessed through another machine, like a superhost. To access these with one command, add the following to the Host entry. <tunnel short name> refers to the <short name> of the Host entry through which you access the machine (e.g., the <host short name> entry uses the superhost’s short name for <tunnel short name>).

Host <short name>
  ...
  ProxyCommand ssh <tunnel short name> -W %h:%p

Once host entries are defined, you can access those machine with:

ssh <short name>

You can also use the short name in rsync, scp, and other commands that use ssh under the hood.

For more details and options, see this tutorial.

We recommend that Loihi system administrators make specific host entries for their system available to all users.

SSH keys

SSH keys allow you to log in to remote machines without providing your password. This is especially useful when accessing a board through a host and superhost, each of which require authentication.

You may already have created an SSH key for another purpose. By default, SSH keys are stored as

  • ~/.ssh/id_rsa (private key)
  • ~/.ssh/id_rsa.pub (public key)

If these files exist when you do ls ~/.ssh, then you already have an SSH key.

If you do not have an SSH key, you can create one with

ssh-keygen

Follow the prompts, using the default values when unsure. We recommend setting a passphrase in case someone obtains your SSH key pair.

Once you have an SSH key pair, you will copy your public key to each machine you want to log into without a password.

ssh-copy-id <host short name>

<host short name> is the name you specified in your SSH config file for that host (e.g., ssh-copy-id loihi-host). You will be prompted for your password in order to copy the key. Once it is copied, try ssh <host short name> to confirm that you can log in without providing a password.

Remote port tunneling

Tunneling a remote port to your local machine allows you to run the Jupyter notebook server or the Nengo GUI server on the superhost or host, but access the web-based interface on your local machine.

To do this, we will create a new terminal window on the local machine that we will keep open while the tunnel is active. In this terminal, do

ssh -L <local port>:localhost:<remote port>

You will then enter an SSH session in which you can start the process that will communicate over <remote port>.

Example 1: Starting a Nengo GUI server on port 8000 of superhost-1, which has a loihi conda environment.

# In a new terminal window on your local machine
ssh -L 8000:localhost:8000 superhost-1
# We are now on superhost-1
source activate loihi
cd ~/nengo-loihi/docs/examples
nengo --port 8000 --no-browser --auto-shutdown 0 --backend nengo_loihi

On your local machine, open http://localhost:8000/ and you should see the Nengo GUI interface.

Example 2: Starting a Jupyter notebook server on port 8080 of superhost-2, which has a loihi virtualenv environment.

# In a new terminal window on your local machine
ssh -L 8080:localhost:8080 superhost-2
# We are now on superhost-2
workon loihi
cd ~/nengo-loihi/docs/examples
jupyter notebook --no-browser --port 8080

The jupyter command should print out a URL of the form http://localhost:8888/?token=<long-strong>, which you can open on your local machine.

Syncing with rsync

If you work on your local machine and push changes to multiple remote superhosts, it is worth spending some time to set up a robust solution for syncing files between your local machine and the superhosts.

rsync is a good option because it is fast (it detects what has changed and only sends changes) and can be configured to ensure that the files on your local machine are the canonical files and are not overwritten by changes made on remotes. rsync also uses SSH under the hood, so the SSH hosts you set up previously can be used.

rsync is available from most package managers (e.g. apt, brew) and in many cases will already be installed on your system.

The basic command that is most useful is

rsync -rtuv --exclude=*.pyc /src/folder /dst/folder
  • -r recurses into subdirectories
  • -t copies and updates file modifications times
  • -u replaces files with the most up-to-date version as determined by modification time
  • -v adds more console output to see what has changed
  • --exclude=*.pyc ensures that *.pyc files are not copied

See also more details and options.

When sending files to a remote host, you may also want to use the --delete option to delete files in the destination folder that have been removed from the source folder.

To simplify rsync usage, you can make small bash functions to make your workflow explicit.

For example, the following bash functions will sync the NxSDK and nengo-loihi folders between the local machine and the user’s home directory on host-1. In this example, the --delete flag is only used on pushing so that files are never deleted from the local machine. The --exclude=*.pyc flag is only used for nengo-loihi because *.pyc files are an important part of the NxSDK source tree. These and other options can be adapted based on your personal workflow.

LOIHI="/path/to/nengo-loihi/"
NXSDK="/path/to/NxSDK/"
push_host1() {
    rsync -rtuv --exclude=*.pyc --delete "$LOIHI" "host-1:nengo-loihi"
    rsync -rtuv --delete "$NXSDK" "host-1:NxSDK"
}
pull_host1() {
    rsync -rtuv --exclude=*.pyc "host-1:nengo-loihi/" "$LOIHI"
    rsync -rtuv "host-1:NxSDK" "$NXSDK"
}

These functions are placed in the ~/.bashrc file and executed at a terminal with

push_host1
pull_host1

Remote editing with SSHFS

If you primarily work with a single remote superhost, SSHFS is a good option that allows you to mount a remote filesystem to your local machine, meaning that you manipulate files as you normally would on your local machine, but those files will actually exist on the remote machine. SSHFS ensures that change you make locally are efficiently sent to the remote.

SSHFS is available from most package managers, including apt and brew.

To mount a remote directory to your local machine, create a directory to mount to, then call sshfs to mount it.

mkdir -p <mount point>
sshfs -o allow_other,defer_permissions <host short name>:<remote directory> <mount point>

When you are done using the remote files, unmount the mount point.

fusermount -u <mount point>

Note

If fusermount is not available and you have sudo access, you can also unmount with

sudo umount <mount point>

As with rsync, since you may do these commands frequently, it can save time to make a short bash function. The following example functions mount and unmount the host-2 ~/loihi directory to the local machine’s ~/remote/host-2 directory.

mount_host2() {
    mkdir -p ~/remote/host-2
    sshfs host-2:loihi ~/remote/host-2
}
unmount_host2() {
    fusermount -u ~/remote/host-2
}

Superhost

Plotting

If you are generating plots with Matplotlib on the superhost or host, you may run into issues due to there being no monitor attached to those machines (i.e., they are “headless”). Rather than plotting to a screen, you can instead save plots as files with plt.savefig. You will also need to configure Matplotlib to use a headless backend by default.

The easiest way to do this is with a matplotlibrc file.

mkdir -p ~/.config/matplotlib
echo "backend: Agg" >> ~/.config/matplotlib/matplotlibrc

IPython / Jupyter

If you want to use the IPython interpreter or the Jupyter notebook on a superhost (e.g., the INRC superhost), you may run into issues due to the network file system (NFS), which does not work well with how IPython and Jupyter track command history. You can configure IPython and Jupyter to instead store command history to memory only.

To do this, start by generating the configuration files.

jupyter notebook --generate-config
ipython profile create

Then add a line to three files to configure the command history for NFS.

echo "c.NotebookNotary.db_file = ':memory:'" >> ~/.jupyter/jupyter_notebook_config.py
echo "c.HistoryAccessor.hist_file = ':memory:'" >> ~/.ipython/profile_default/ipython_config.py
echo "c.HistoryAccessor.hist_file = ':memory:'" >> ~/.ipython/profile_default/ipython_kernel_config.py

Slurm cheatsheet

Most Loihi superhosts use Slurm to schedule and distribute jobs to Loihi hosts. Below are the commands that Slurm makes available and what they do.

sinfo
Check the status (availability) of connected hosts.
squeue
Check the status of your jobs.
scancel <jobid>
Kill one of your jobs.
scancel --user=<username>
Kill all of your jobs.
sudo scontrol update nodename="<nodename>" state="idle"

Mark a Loihi host as “idle”, which places it in the pool of available hosts to be used. Use this when a Loihi host that was down comes back up.

Note

This should only be done by a system administrator.

Use Slurm by default

Most superhosts use Slurm to run models on the host. Normally you can opt in to executing a command with

SLURM=1 my-command

However, you will usually want to use Slurm, so to switch to an opt-out setup, open your shell configuration file in a text editor (usually ~/.bashrc), and add the following line to the end of the file.

export SLURM=1

Once making this change you can opt out of using Slurm by executing a command with

SLURM=0 my-command

Running large models

Normally you do not need to do anything other than setting the SLURM environment variable to run a model on Slurm. However, in some situation Slurm may kill your job due to long run times or other factors.

Custom Slurm partitions can be used to run your job with different sets of restrictions. Your system administrator will have to set up the partition. You can see a list of all partitions and nodes with sinfo.

To run a job with the loihiinf partition, set the environment variable PARTITION. For example, you can run bigmodel.py using this partition with

PARTITION=loihiinf python bigmodel.py

Similarly, if you wish to use a particular board (called a “node” in Slurm), set the BOARD environment variable. For example, to run model.py on the loihimh board, do

BOARD=loihimh python model.py