This is a _very_ early draft.

-----

MATLAB is an excellent match for Condor. Millions of MATLAB jobs, possibly tens of millions, have been successfully run under Condor over the years.  The specifics of working with MATLAB will vary from site to site, but here are some general guidelines.

This assumes basic familiarity with MATLAB and Condor. It assumes that you can set up and maintain at least a small Condor pool.

{section: Licensing}

Perhaps the biggest challenge to running MATLAB under Condor is licensing. MATLAB is proprietary software with strict licensing terms.  You might have one or two licenses for your desktop computers, but to run hundreds of simultaneous MATLAB jobs you would require hundreds of licenses.

Your institution may already have acquired suitable licensing for MATLAB.  If you have a fixed number of licenses available, Condor's {link:http://www.cs.wisc.edu/condor/manual/v7.6/3_13Setting_Up.html#sec:Concurrency-Limits Concurrency Limit support} can help.

Another option uses the MATLAB Compiler to create an executable that can be run with the MATLAB Compiler Runtime (MCR).  The MATLAB Compiler is an optional toolbox for MATLAB.  In general, executables created with the MATLAB Compiler are not subject to MATLAB's license; you are free to run as many in parallel as possible. _Check your MATLAB licensing to confirm this._

If you are using third party MATLAB add-ons, you will need to check the licensing on them as well.


{section: Executables}

The MATLAB executable and supporting libraries must be made available on any computers on which the Condor jobs might run.
When using the MATLAB Compiler, instead of the full MATLAB executable and supporting libraries, the MCR is needed.  The general techniques  for making the MCR available are the same.
Accomplish this by one of

*: *Install MATLAB on each computer that may run a MATLAB Condor job.*

_:If you install MATLAB locally on each computer, we recommend placing MATLAB in the _same location_ on each computer.  That way individual jobs can easily find it. Here is a portion of a user's submit description file:

{code}
executable = my_task
arguments = $$(MATLAB_PATH)
transfer_input_files= my_task.m
queue
{endcode}

_:where =my_task= would then be a script that did something like this:

{code}
#! /bin/sh
exec /opt/matlab/bin/matlab -nodisplay ./my_task.m
{endcode}

_:If MATLAB will be in _different locations_ on each computer,
use the configuration variable {link:http://www.cs.wisc.edu/condor/manual/v7.6/3_3Configuration.html#param:SubsysAttrs STARTD_ATTRS} in the local configuration file of each machine to advertise the correct location. Then, the job can use a {link:http://www.cs.wisc.edu/condor/manual/v7.6/condor_submit.html#73792 $$} expression to find the executable.  For example, the local configuration file might say:

{code}
MATLAB_PATH  = /opt/matlab/bin
STARTD_ATTRS = MATLAB_PATH
{endcode}

_:A portion of a user's submit description file:

{code}
executable = my_task
arguments = $$(MATLAB_PATH)
transfer_input_files= my_task.m
queue
{endcode}

_:where =my_task= would then be a script that did something like this:

{code}
#! /bin/sh
exec "$1"/matlab -nodisplay ./my_task.m
{endcode}

_:The batch scripts for Windows platforms are similar.

*: *Install MATLAB on a shared file system, such that it is accessible by each computer that may run a MATLAB Condor job.*

_:Installing on a shared filesystem is identical to installing it on each local computer, but may be less complicated for administration.


*: *transfer the MATLAB executable (and supporting libraries) along with the Condor job.*

_:To bring Matlab along yourself, you would need to package it up, bring it along (transfer_input_files), then have a script unpack Matlab and start it.  Matlab is a large piece of software, and this could be slow. It will also temporarily use a bunch of disk space with a copy of Matlab.  If multiple Matlab jobs run on the same computer simultaneously, multiple copies of Matlab will be installed at once.  Generally speaking this is not recommended, although it is more practical for the MCR.


To compile "foo.m" with the MATLAB Compiler, you would use a command like the following.  The various options are explained further below; -R simply tells Matlab to behave as though the next option was passed in when the job is started.
{code}
mcc -m -R -singleCompThread -R -nodisplay -R -nojvm -nocache foo.m
{endcode}


{section: Invoking}

Matlab may try to create a graphical environment.  Condor does not support graphical environments; it doesn't make sense to open up a user interface for a job that won't have a user directly looking at it.  You may need some combination of -nosplash, -nodisplay, and possibly -nojvm to stop Matlab from creating a graphical environment. This should not be necessary for Matlab Compiler compiled jobs.

Unless you have special arrangements to use multiple CPU cores, you will want -singleCompThread so that Matlab only uses a single core.

|-nosplash         | Disable splash screen. (No GUI support in Condor)|
|-nodisplay        | Disable GUI. (No GUI support in Condor)|
|-nojvm            | Disable GUI? Eliminate unnecessary Java (faster?)|
|-singleCompThread | Only use one CPU core (play nicely when sharing computer)|



{section: Parallelism}

In the most common configuration, Condor does not directly support "parallel" jobs, jobs that might use a system like MPI or multiple threads to take advantage of multiple CPUs at once.  Condor can launch jobs that use multiple processes or threads, but by default Condor will offer them a single CPU core to run on.  (They may get lucky and be able to use more than one CPU core on a computer, but that should not be relied on.)

A local installation may provide additional options for parallel, usually in the form of offering a job two or more CPUs on a single computer.  Local administrators should be able to describe available functionality.

Given the default configuration, it is usually better to break your work down into multiple independent jobs.  For example, if you are processing 10,000 images, instead of a single Matlab job that processes them, perhaps you could have 10,000 jobs that each process 1 image.  Condor is then able to schedule your jobs across multiple computers or at least multiple cores on a single computer, giving you the speed benefits of parallelism.

For older Matlab (Possibly pre 2011?), to ensure that Matlab only uses one core, put this in your Matlab script:

{code}
lastN = maxNumCompThreads(1);   (Pre r2009bsp1)
{endcode}

If you're using the Matlab Compiler, but want to use multiple threads when doing development, you could use something like this to limit Matlab to one thread only for compiled versions:

{code}
if isdeployed
    lastN = maxNumCompThreads(1);
end
{endcode}

If you do the above with R2009sp1 and newer and also use the -R -singleCompThread it will error out.

*: *TODO*: Is the lastN necessary? Seems unlikely, unless Matlab gets cranky when return values are ignored.

The above does not work on newer versions of Matlab, as maxNumCompThreads is deprecated.  Instead, pass the -singleCompThread option.  If you are using mcc (the Matlab compiler), add "-R -singleCompThread" to your compiler options.

The best you can do is prevent the compiled job from using one thread per core. It will still have 5 threads with all the time on one of them. Java aps will use a few more threads. But you will have less then one thread per core which is what it will do on its own.

{section: Example}

This example assumes that Matlab is available in /opt/Matlab/bin.

*COMPLETELY UNTESTED*
*:*TODO*: Is the DISPLAY=:0.0 required? Seems unlikely.
*:*TODO*: Is the HOME=. required?
*:*TODO*: Is the MATLAB_PREF=. required?

{code}
executable = /opt/Matlab/bin/matlab
arguments = -nodisplay -nojvm -singleCompThread  my-script.m
transfer_input_files = my-script.m
output = my-script.output
error = my-script.error
log = my-script.log
environment = "DISPLAY=:0.0 HOME=. MATLAB_PREF=."
queue
{endcode}




{section: Additional Resources}

Many other sites are using Matlab under Condor.  Here are links to the documentation from just a few.

*: {link:http://www.cae.wisc.edu/matlab-condor University of Wisconsin - Madison - CAE}
*: {link:http://www.liv.ac.uk/csd/escience/condor/matlab/old_instructions.htm University of Liverpool}