Matlab on Pegasus

Interactive Mode

There are several ways to run MATLAB commands/jobs interactively, with or without the graphical interface.

Graphical Interface Mode

To run MATLAB using graphical interface mode, connect with display forwarding. For more information about display forwarding, see Forwarding the Display.

Load and launch MATLAB on one of the interactive compute nodes as shown below. If you belong to more than one project, specify the projectID as well.

[username@pegasus ~]$ module load matlab
[username@pegasus ~]$ bsub -Is -q interactive -XF -P projectID matlab

Once the interactive MATLAB graphical desktop is loaded, you can then run MATLAB commands or scripts in the MATLAB command window. The results will be shown in the MATLAB command window and the figure/plot will be displayed in new graphical windows on your computer. See examples below.

>> x = rand(1,100);
>> plot(x);
>> x = [0: pi/10: pi];
>> y = sin(x);
>> z = cos(x);
>> figure;
>> plot(x, y);
>> hold('on');
>> plot(x, z, '--');

Graphical Interactive Mode with no graphical desktop window

Running MATLAB in a full graphical mode may get slow depending on the network load. Running it with -nodesktop option will use your current terminal window (in Linux/Unix) as a desktop, while allowing you still to use graphics for figures and editor.

[username@pegasus ~]$ module load matlab
[username@pegasus ~]$ bsub -Is -q interactive -XF -P projectID matlab -nodesktop

Non-Graphical interactive Mode

If your MATLAB commands/jobs do not need to show graphics such as figures and plots, or to use a built-in script editor, run the MATLAB in the non-graphical interactive mode with -nodisplay.

Open a regular ssh connection to Pegasus.

[username@pegasus ~]$ module load matlab
[username@pegasus ~]$ bsub -Is -q interactive -P projectID matlab -nodisplay

This will bring up the MATLAB command window:

                            < M A T L A B (R) >
                  Copyright 1984-2018 The MathWorks, Inc.
                    R2018a ( 64-bit (glnxa64)
                             February 23, 2018

No window system found.  Java option 'Desktop' ignored.

To get started, type one of these: helpwin, helpdesk, or demo.
For product information, visit

To exit, type exit or quit. Again, remember to import the prepared LSF configuration file mentioned above if you want to use MATLAB parallel computing.

Batch Processing

For off-line non-interactive computations, submit the MATLAB script to the LSF scheduler using the bsub command. For more information about job scheduling, see Scheduling Jobs. Example single-processor job submission:

[username@pegasus ~]@ bsub < example.job


#BSUB -J example
#BSUB -q general
#BSUB -P projectID
#BSUB -n 1
#BSUB -o example.o%J
#BSUB -e example.e%J
matlab -nodisplay -r my_script

In this example, “my_script” corresponds to “my_script.m” in the current working directory.

After the job is finished, the results will be saved in the output file named “example.o######” where “######” is a jobID number assigned by LSF when you submit your job.

Parallel Computations

MATLAB’s Parallel Computing Toolbox™ and Distributed Computing Server™ let users run MATLAB programs and Simulink models on multi-core and/or multi-node computer clusters. The Parallel Computing Toolbox, a toolbox of parallel-enabled functions that abstracts away the complexity of parallel programming, enables the user to write code that scales across multiple compute cores and/or processors without needing any modification. Furthermore, the Parallel Computing Toolbox defines the jobs and their distribution to MATLAB computational engines or workers. The MATLAB Distributed Computing Server is responsible for the execution of the jobs, and interfaces with resource schedulers such as LSF, effectively mapping each MATLAB worker to the available cores of multicore standalone/cluster computers.

Single-node parallel MATLAB jobs (up to 16 cpus)

The MATLAB Distributed Computing Server™ can be used to provide up to 16 MATLAB computational engines or workers on a single node on Pegasus. You may get up to 15 workers on the general queue, and up to 16 on the parallel one. For more information about queue and parallel resource distribution requirements, see Scheduling Jobs.

Documentation from MATLAB outlines strategies and tools from the Parallel Computing Toolbox that help adapt your script for multi-processor calculations. One of the tools available is a parallel construct of the ubiquitous for loop, which is named the parfor loop, and the syntax for its use is as shown in the script right below. Essentially, what would have been a set of sequential operations on a single processor can now be a set of parallel operations over a parallel pool (parpool) of 16 MATLAB workers.

% dct_example.m
% Distributed Computing Toolbox (DCT)
% Example: Print datestamp within a parallel "parfor" loop
%% Create a parallel pool of workers on the current working node:
% The test loop size
N = 40;
tstart = tic();
  ixstamp = sprintf('Iteration %d at %s\n', ix, datestr(now));
toctime= sprintf('Time used is %d seconds', cputime);
%% delete current parallel pool:

Multi-node parallel MATLAB jobs (16-32 cpus)

MATLAB licenses the MATLAB Distributed Computer Engine™ for running multi-processor jobs that involve 16+ cpus and more than a single node. We have up to 32 licenses available on Pegasus, and this makes it possible to run jobs on up to 32 cores. The first thing that needs to be done is to make sure that Pegasus, running LSF, is discoverable to MATLAB. To do this, the user has the MATLAB client use the cluster configuration file /share/opt/MATLAB/etc/LSF1.settings to create a cluster profile (for themself). This is done as follows:

[username@pegasus ~]$ matlab -nodisplay -r "parallel.importProfile('/share/opt/MATLAB/etc/LSF1.settings')"
[username@pegasus ~] >> exit
[username@pegasus ~]$ reset

This command only needs to be run once. It imports the cluster profile named ‘LSF1’ that is configured to use up to 32 MatlabWorkers and to submit MATLAB jobs to the parallel Pegasus queue. This profile does not have a projectID associated with the job, and you may need to coordinate the project name for the LSF job submission. This can be done by running the following script conf_lsf1_project_id.m (only once!) during your matlab session:

%% conf_lsf1_project_id.m
%% Verify that LSF1 profile exists, and indicate the current default profile:
[allProfiles,defaultProfile] = parallel.clusterProfiles()
%% Define the current cluster object using LSF1 profile
%% View current submit arguments:
%% Set new submit arguments, change projectID below to your current valid project:
set(myCluster,'SubmitArguments','-q general -P projectID')
%% Save the cluster profile:
%% Set the 'LSF1' to be used as a default cluster profile instead of a 'local'
%% Verify the current profiles and the default:
[allProfiles,defaultProfile] = parallel.clusterProfiles()

The multi-node parallel jobs must be submitted to the **parallel* queue with the appropriate ptile resource distribution.* For more information about queue and resource distribution requirements, see Scheduling Jobs.

The above script also reviews your current settings of the cluster profiles. You can now use the cluster profile for distributed calculations on up to 32 CPUs, for example, to create a pool of MatlabWorkers for a parfor loop:

% dce_example.m
% Distributed Computing Engine (DCE)
% Example: Print datestamp within a parallel "parfor" loop
% Maximum number of MatlabWorkers is 32 (number of MATLAB DCE Licenses)
% The test loop size
N = 40;
tstart = tic();
  ixstamp = sprintf('Iteration %d at %s\n', ix, datestr(now));
toctime= sprintf('Time used is %d seconds', cputime);

Please see MATLAB documentation on more ways to parallelize your code.

There may be other people running Distributed Computing Engine and thus using several licenses. Please check the license count as following (all in a single line):

[username@pegasus ~]$ /share/opt/MATLAB/R2013a/etc/lmstat -S MLM -c /share/opt/MATLAB/R2013a/licenses/network.lic

Find the information about numbers of licenses used for the “Users of MATLAB_Distrib_Comp_Engine”, “Users of MATLAB”, and “Users of Distrib_Computing_Toolbox”.

Note on Matlab cluster configurations

After importing the new cluster profile, it will remain in your available cluster profiles. Validate using the parallel.clusterProfiles() function. You can create, change, and save profiles using SaveProfile and SaveAsProfile methods on a cluster object. In the examples, “myCluster” is the cluster object. You can also create, import, export, delete, and modify the profiles through the “Cluster Profile Manager” accessible via MATLAB menu in a graphical interface. It is accessed from the “HOME” tab in the GUI desktop window under “ENVIRONMENT” section: ->“Parallel”->“Manage Cluster Profiles”

Cluster Profile Manager

Cluster Profile Manager

You can also create your own LSF configuration from the Cluster Profile Manager. Choose “Add”->“Custom”->“3RD PARTY CLUSTER PROFILE”->“LSF” as shown below:

Cluster Profile Manager: new LSF cluster

Cluster Profile Manager: new LSF cluster

… and configure to your needs:

New LSF cluster in Matlab

New LSF cluster in Matlab


When launching matlab for the first time as an interactive job you may get a connection error like so:

(base) [sxs3396@login4 ~]$  bsub -Is -q interactive -XF -P hpc matlab
Job is submitted to <hpc> project.
Job <28645954> is submitted to queue <interactive>.
<<ssh X11 forwarding job>>
<<Waiting for dispatch ...>>
Someone could be eavesdropping on you right now (man-in-the-middle attack)!
It is also possible that a host key has just been changed.
The fingerprint for the ECDSA key sent by the remote host is
Please contact your system administrator.
Add correct host key in /nethome/sxs3396/.ssh/known_hosts to get rid of this message.
Offending ECDSA key in /nethome/sxs3396/.ssh/known_hosts:1
Password authentication is disabled to avoid man-in-the-middle attacks.
Keyboard-interactive authentication is disabled to avoid man-in-the-middle attacks.
X11 forwarding is disabled to avoid man-in-the-middle attacks.
Permission denied (publickey,gssapi-keyex,gssapi-with-mic,password).
^CJob <28645954> is being terminated

You can fix this by running the following command from login4:

[sxs3396@login4 ~]$ ssh-keygen -R