Starting the IPython controller and engines

To use IPython for parallel computing, you need to start one instance of the controller and one or more instances of the engine. The controller and each engine can run on different machines or on the same machine. Because of this, there are many different possibilities.

Broadly speaking, there are two ways of going about starting a controller and engines:

  • In an automated manner using the ipcluster command.
  • In a more manual way using the ipcontroller and ipengine commands.

This document describes both of these methods. We recommend that new users start with the ipcluster command as it simplifies many common usage cases.

General considerations

Before delving into the details about how you can start a controller and engines using the various methods, we outline some of the general issues that come up when starting the controller and engines. These things come up no matter which method you use to start your IPython cluster.

Let’s say that you want to start the controller on host0 and engines on hosts host1-hostn. The following steps are then required:

  1. Start the controller on host0 by running ipcontroller on host0.
  2. Move the FURL file (ipcontroller-engine.furl) created by the controller from host0 to hosts host1-hostn.
  3. Start the engines on hosts host1-hostn by running ipengine. This command has to be told where the FURL file (ipcontroller-engine.furl) is located.

At this point, the controller and engines will be connected. By default, the FURL files created by the controller are put into the ~/.ipython/security directory. If the engines share a filesystem with the controller, step 2 can be skipped as the engines will automatically look at that location.

The final step required required to actually use the running controller from a client is to move the FURL files ipcontroller-mec.furl and ipcontroller-tc.furl from host0 to the host where the clients will be run. If these file are put into the ~/.ipython/security directory of the client’s host, they will be found automatically. Otherwise, the full path to them has to be passed to the client’s constructor.

Using ipcluster

The ipcluster command provides a simple way of starting a controller and engines in the following situations:

  1. When the controller and engines are all run on localhost. This is useful for testing or running on a multicore computer.
  2. When engines are started using the mpirun command that comes with most MPI [MPI] implementations
  3. When engines are started using the PBS [PBS] batch system.
  4. When the controller is started on localhost and the engines are started on remote nodes using ssh.


It is also possible for advanced users to add support to ipcluster for starting controllers and engines using other methods (like Sun’s Grid Engine for example).


Currently ipcluster requires that the ~/.ipython/security directory live on a shared filesystem that is seen by both the controller and engines. If you don’t have a shared file system you will need to use ipcontroller and ipengine directly. This constraint can be relaxed if you are using the ssh method to start the cluster.

Underneath the hood, ipcluster just uses ipcontroller and ipengine to perform the steps described above.

Using ipcluster in local mode

To start one controller and 4 engines on localhost, just do:

$ ipcluster local -n 4

To see other command line options for the local mode, do:

$ ipcluster local -h

Using ipcluster in mpiexec/mpirun mode

The mpiexec/mpirun mode is useful if you:

  1. Have MPI installed.
  2. Your systems are configured to use the mpiexec or mpirun commands to start MPI processes.


The preferred command to use is mpiexec. However, we also support mpirun for backwards compatibility. The underlying logic used is exactly the same, the only difference being the name of the command line program that is called.

If these are satisfied, you can start an IPython cluster using:

$ ipcluster mpiexec -n 4

This does the following:

  1. Starts the IPython controller on current host.
  2. Uses mpiexec to start 4 engines.

On newer MPI implementations (such as OpenMPI), this will work even if you don’t make any calls to MPI or call MPI_Init(). However, older MPI implementations actually require each process to call MPI_Init() upon starting. The easiest way of having this done is to install the mpi4py [mpi4py] package and then call ipcluster with the --mpi option:

$ ipcluster mpiexec -n 4 --mpi=mpi4py

Unfortunately, even this won’t work for some MPI implementations. If you are having problems with this, you will likely have to use a custom Python executable that itself calls MPI_Init() at the appropriate time. Fortunately, mpi4py comes with such a custom Python executable that is easy to install and use. However, this custom Python executable approach will not work with ipcluster currently.

Additional command line options for this mode can be found by doing:

$ ipcluster mpiexec -h

More details on using MPI with IPython can be found here.

Using ipcluster in PBS mode

The PBS mode uses the Portable Batch System [PBS] to start the engines. To use this mode, you first need to create a PBS script template that will be used to start the engines. Here is a sample PBS script template:

#PBS -N ipython
#PBS -j oe
#PBS -l walltime=00:10:00
#PBS -l nodes=${n/4}:ppn=4
#PBS -q parallel

export PATH=$$HOME/usr/local/bin
export PYTHONPATH=$$HOME/usr/local/lib/python2.4/site-packages
/usr/local/bin/mpiexec -n ${n} ipengine --logfile=$$PBS_O_WORKDIR/ipengine

There are a few important points about this template:

  1. This template will be rendered at runtime using IPython’s Itpl template engine.
  2. Instead of putting in the actual number of engines, use the notation ${n} to indicate the number of engines to be started. You can also uses expressions like ${n/4} in the template to indicate the number of nodes.
  3. Because $ is a special character used by the template engine, you must escape any $ by using $$. This is important when referring to environment variables in the template.
  4. Any options to ipengine should be given in the batch script template.
  5. Depending on the configuration of you system, you may have to set environment variables in the script template.

Once you have created such a script, save it with a name like pbs.template. Now you are ready to start your job:

$ ipcluster pbs -n 128 --pbs-script=pbs.template

Additional command line options for this mode can be found by doing:

$ ipcluster pbs -h

Using ipcluster in SSH mode

The SSH mode uses ssh to execute ipengine on remote nodes and the ipcontroller on localhost.

When using using this mode it highly recommended that you have set up SSH keys and are using ssh-agent [SSH] for password-less logins.

To use this mode you need a python file describing the cluster, here is an example of such a “clusterfile”:

send_furl = True
engines = { '' : 2,
            '' : 5,
            '' : 1,
            '' : 8 }

Since this is a regular python file usual python syntax applies. Things to note:

  • The engines dict, where the keys is the host we want to run engines on and the value is the number of engines to run on that host.
  • send_furl can either be True or False, if True it will copy over the furl needed for ipengine to each host.

The --clusterfile command line option lets you specify the file to use for the cluster definition. Once you have your cluster file and you can ssh into the remote hosts with out an password you are ready to start your cluster like so:

$ ipcluster ssh --clusterfile /path/to/my/

Two helper shell scripts are used to start and stop ipengine on remote hosts:


Defaults for both of these are contained in the source code for ipcluster. The default scripts are written to a local file in a tmep directory and then copied to a temp directory on the remote host and executed from there. On most Unix, Linux and OS X systems this is /tmp.

The default is the following:

"$@" &> /dev/null &
echo $!

If you want to use a custom script you need to use the --sshx option and specify the file to use. Using a custom file could be helpful when you need to setup the environment on the remote host before executing ipengine.

For a detailed options list:

$ ipcluster ssh -h

Current limitations of the SSH mode of ipcluster are:

  • Untested on Windows. Would require a working ssh on Windows. Also, we are using shell scripts to setup and execute commands on remote hosts.
  • ipcontroller is started on localhost, with no option to start it on a remote node.

Using the ipcontroller and ipengine commands

It is also possible to use the ipcontroller and ipengine commands to start your controller and engines. This approach gives you full control over all aspects of the startup process.

Starting the controller and engine on your local machine

To use ipcontroller and ipengine to start things on your local machine, do the following.

First start the controller:

$ ipcontroller

Next, start however many instances of the engine you want using (repeatedly) the command:

$ ipengine

The engines should start and automatically connect to the controller using the FURL files in ~./ipython/security. You are now ready to use the controller and engines from IPython.


The order of the above operations is very important. You must start the controller before the engines, since the engines connect to the controller as they get started.


On some platforms (OS X), to put the controller and engine into the background you may need to give these commands in the form (ipcontroller &) and (ipengine &) (with the parentheses) for them to work properly.

Starting the controller and engines on different hosts

When the controller and engines are running on different hosts, things are slightly more complicated, but the underlying ideas are the same:

  1. Start the controller on a host using ipcontroller.
  2. Copy ipcontroller-engine.furl from ~./ipython/security on the controller’s host to the host where the engines will run.
  3. Use ipengine on the engine’s hosts to start the engines.

The only thing you have to be careful of is to tell ipengine where the ipcontroller-engine.furl file is located. There are two ways you can do this:

  • Put ipcontroller-engine.furl in the ~./ipython/security directory on the engine’s host, where it will be found automatically.
  • Call ipengine with the --furl-file=full_path_to_the_file flag.

The --furl-file flag works like this:

$ ipengine --furl-file=/path/to/my/ipcontroller-engine.furl


If the controller’s and engine’s hosts all have a shared file system (~./ipython/security is the same on all of them), then things will just work!

Make FURL files persistent

At fist glance it may seem that that managing the FURL files is a bit annoying. Going back to the house and key analogy, copying the FURL around each time you start the controller is like having to make a new key every time you want to unlock the door and enter your house. As with your house, you want to be able to create the key (or FURL file) once, and then simply use it at any point in the future.

This is possible, but before you do this, you must remove any old FURL files in the ~/.ipython/security directory.


You must remove old FURL files before using persistent FURL files.

Then, The only thing you have to do is decide what ports the controller will listen on for the engines and clients. This is done as follows:

$ ipcontroller -r --client-port=10101 --engine-port=10102

These options also work with all of the various modes of ipcluster:

$ ipcluster local -n 2 -r --client-port=10101 --engine-port=10102

Then, just copy the furl files over the first time and you are set. You can start and stop the controller and engines any many times as you want in the future, just make sure to tell the controller to use the same ports.


You may ask the question: what ports does the controller listen on if you don’t tell is to use specific ones? The default is to use high random port numbers. We do this for two reasons: i) to increase security through obscurity and ii) to multiple controllers on a given host to start and automatically use different ports.

Log files

All of the components of IPython have log files associated with them. These log files can be extremely useful in debugging problems with IPython and can be found in the directory ~/.ipython/log. Sending the log files to us will often help us to debug any problems.

[PBS](1, 2) Portable Batch System.