# MatLab CLI

(Difference between revisions)

While MATLAB is typically used via GUI workspace environment on a local desktop, MATLAB can be accessed from a command line environment in order to call MATLAB scripts from other scripts, issue commands to a running instances, or simply to support using a text-based terminal for users who prefer or need that functionality.

The instructions below describe command-line MATLAB interaction for the HPC environment on Cheaha.

Please see the MATLAB application page for more information and a general overview of MATLAB and its use at UAB.

## Contents

### MATLAB Versions

Use the 'module' command to view a list of available MATLAB versions. If the version that you require isn't listed, please open a help desk ticket to request the installation.

The following is an example output of the command and doesn't necessarily represent the currently installed versions:

$module avail mathworks ------------------------------------ /etc/modulefiles ------------------------------------- mathworks/R2010b mathworks/R2010a mathworks/R2010b mathworks/R2009b mathworks/R2009a  ### Simple MATLAB Test A simple test to verify that the MATLAB client on Cheaha can check out a license from your server (or from the campus license server 27000@lmgr.uabgrid.uab.edu ). Set up your environment with the command: $ module load mathworks/R2010b


As a test, you can run MatLab and access your license server with

$matlab -c port@license-server -nodesktop -nojvm -r 'rand, pause(0), exit'  For example: $ module load mathworks/R2010b
$matlab -c 27000@lmgr.uabgrid.uab.edu -nodesktop -nojvm -r 'rand, pause(0), exit' < M A T L A B (R) > Copyright 1984-2010 The MathWorks, Inc. Version 7.11.0.584 (R2010b) 64-bit (glnxa64) August 16, 2010 To get started, type one of these: helpwin, helpdesk, or demo. For product information, visit www.mathworks.com. ans = 0.8147  This will start matlab without a graphical display and without Java support. This is good just to verify things work, but do not run any significant computations on the Cheaha head node! MatLab computational work must be run on the compute nodes by submitting a job submission script to the SGE scheduler or by using the Parallel Computing Toolbox on your desktop. ### Serial MATLAB Serial MATLAB jobs have the following characteristics: * Consumes one of your client licenses for the duration of the job * Does not use the distributed licenses available on cheaha * Does not require the Parallel Computing Toolbox * Restricted to a single CPU core (slot)  See the next section for an example using the distributed computing license. Create a job script "matlabtest.qsub" making sure to change: * YOUR_EMAIL_ADDRESS * h_rt and s_rt to appropriate hard and soft runtime limits * vf to the maximum amount of memory that your job will use  Note, the matlab command switch '-nojvm' dramatically decreases the amount of RAM needed to start MATLAB. The work performed by your job will determine whether or not it can be run with '-nojvm' $ mkdir -p $UABGRID_SCRATCH/jobs/matlab/serial01/output$ cd $UABGRID_SCRATCH/jobs/matlab/serial01  #!/bin/bash #$ -S /bin/bash
#$-cwd # #$ -N serialMatlab
#$-l h_rt=00:10:00,s_rt=00:08:00,vf=2G #$ -j y
#
#$-M YOUR_EMAIL_ADDRESS #$ -m eas
#
#$-V matlab -c 27000@lmgr.uabgrid.uab.edu -nodisplay -nojvm < matlab-script  Then submit the script to the scheduler with $ cd $UABGRID_SCRATCH/jobs/matlab/serial01$ qsub matlabtest.qsub


Check on it with qstat.

$qstat -u$USER


### Distributed MATLAB

These instructions provide an example of how to create and submit a distributed MATLAB job on cheaha.

Distributed MATLAB jobs use the following licenses:

• MATLAB client license with the Parallel Computing Toolbox - Uses 1 client license
• The Cheaha Distributed Computing license - 1 DCS license per cpu slot

The client license will only be needed for as long as it takes MATLAB to start the job on the compute nodes (unless you keep the client open, for example using "waitForState(job)" in your MATLAB script). This is mostly relevant if you are using a client license from a source other than the UAB MATLAB site license where there are a limited number of licenses available.

The instructions are a work in progress, so please contact Research Computing support with any questions or corrections.

First, create the working directory for the job

$mkdir -p$UABGRID_SCRATCH/jobs/matlab/distrib01/output
$cd$UABGRID_SCRATCH/jobs/matlab/distrib01



Next, create a simple 2 task distributed MATLAB script called "sharedDistrib01.m" make sure to change:

* email to your email address
* s_rt to an appropriate soft wall time limit
* h_rt to the maximum wall time for your job
* vf to the maximum memory needed for each task
* outputDirectory to the directory where results should be stored


Don't make any changes to the section labeled "Configure the scheduler"

% Always set these variables
matlab_ver      = 'R2010b';    % (MATLAB release supported by your license) R2009a R2009b R2010a
email_opt       = 'eas';       % qsub email options
s_rt            = '00:05:00';  % soft wall time
h_rt            = '00:07:00';  % hard wall time
vf              = '1G';        % Amount of memory need per task
scratch         = getenv('UABGRID_SCRATCH');
outputDirectory  = [scratch, '/jobs/matlab/distrib01/output'];

% Configure the scheduler
sched = findResource('scheduler', 'type', 'generic');
set(sched, 'DataLocation'       , outputDirectory);
set(sched, 'ClusterMatlabRoot', ['/share/apps/mathworks/', matlab_ver]);
set(sched, 'HasSharedFilesystem',  true);
set(sched, 'ClusterOsType'      , 'unix');
set(sched, 'SubmitFcn', {@sgeSubmitFcn});
set(sched, 'DestroyJobFcn', {@sgeDestroyJob});
set(sched, 'GetJobStateFcn', {@sgeGetJobState});
sge_options = ['-pe matlab 1 -l matlab_dcs=1,vf=', vf, ',h_rt=', h_rt, ',s_rt=', s_rt, ' -m ', email_opt, ' -M ', email];
SGEClusterInfo.setExtraParameter(sge_options);
get(sched)
job = createJob(sched);

% start of user specific commands

submit(job)


Running the MATLAB script will submit 2 SGE single slot (CPU) jobs, one for each task. The Parallel Computing Toolbox requires Java VM, so notice that for this job we do not include the "-nojvm" switch!

$module load mathworks/R2010a$ matlab -c port@license-server -nodisplay < sharedDistrib01.m


Check qstat to see that the scheduler now has 2 jobs running, one for each task

$qstat -u$USER

job-ID  prior   name       user         state submit/start at     queue                          slots ja-task-ID
-----------------------------------------------------------------------------------------------------------------
110839 0.50167 Job1.1     jdoe         r     03/10/2010 16:32:37 all.q@compute-0-12.local           1
110840 0.50083 Job1.2     jdoe         r     03/10/2010 16:32:37 all.q@compute-0-12.local           1


The job output can be found in the "output" directory

### Parallel MATLAB

These instructions provide an example of how to create and submit a parallel MATLAB job on cheaha. Parallel MATLAB jobs require two separate licenses:

* Your own client license that includes the Parallel Computing Toolbox
* The Cheaha 128 node Distributed Computing license


The client license will only be needed for as long as it takes MATLAB to start the job on the compute nodes (unless you keep the client open, for example using "waitForState(job)" in your MATLAB script).

Check out this MATLAB Help Page for a quick overview of using parallel code in your MATLAB scripts.

First, create the working directory for the job

$mkdir -p$UABGRID_SCRATCH/jobs/matlab/paralle01/output
$cd$UABGRID_SCRATCH/jobs/matlab/parallel01



Next, create a simple 4 slot parallel MATLAB script called "sharedPar01.m" make sure to change:

* email to your email address
* s_rt to an appropriate soft wall time limit
* h_rt to the maximum wall time for your job
* vf to the maximum memory needed for each task
* outputDirectory to the directory where results should be stored


Don't make any changes to the section labeled "Configure the scheduler"

% Always set these variables
matlab_ver      = 'R2010a';    % (MATLAB release supported by your license) R2009a R2009b R2010a
email_opt       = 'eas';       % qsub email options
s_rt            = '00:05:00';  % soft wall time
h_rt            = '00:07:00';  % hard wall time
vf        = '1G';        % Amount of memory need per task
min_cpu_slots   = 4;           % Minimum number of cpu slots needed for the parallel job
max_cpu_slots   = 8;           % Maximum number of cpu slots needed for the parallel job
scratch         = getenv('UABGRID_SCRATCH');
outputDirectory = [scratch, '/jobs/matlab/parallel01/output'];

% Configure the scheduler
sched = findResource('scheduler', 'type', 'generic');
set(sched, 'DataLocation'       , outputDirectory);
set(sched, 'ClusterMatlabRoot', ['/share/apps/mathworks/', matlab_ver]);
set(sched, 'HasSharedFilesystem',  true);
set(sched, 'ClusterOsType'      , 'unix');
set(sched, 'ParallelSubmitFcn', {@sgeParallelSubmitFcn});
set(sched, 'DestroyJobFcn', {@sgeDestroyJob});
set(sched, 'GetJobStateFcn', {@sgeGetJobState});
sge_options = ['-l matlab_dcs=1,vf=', vf, ',h_rt=', h_rt, ',s_rt=', s_rt, ' -m ', email_opt, ' -M ', email];
SGEClusterInfo.setExtraParameter(sge_options);
get(sched)
pjob = createParallelJob(sched);

% start of user specific commands
set(pjob, 'MinimumNumberOfWorkers', min_cpu_slots);
set(pjob, 'MaximumNumberOfWorkers', max_cpu_slots);

submit(pjob)


Running the MATLAB script will submit 1 SGE job requesting 4 slots (cpu cores). The Parallel Computing Toolbox requires Java VM, so notice that for this job we do not include the "-nojvm" switch!

$module load mathworks/R2010a$ matlab -c port@license-server -nodisplay < sharedPar01.m


Check qstat to see that the scheduler now has 2 jobs running, one for each task

$qstat -u$USER

job-ID  prior   name	   user         state submit/start at     queue                          slots ja-task-ID
-----------------------------------------------------------------------------------------------------------------
110857 0.00000 Job1	   jdoe         r     03/10/2010 17:20:08                                    4



The job output can be found in the "output" directory

### Matlabpool/ParFor Parallel Example

This example will utilize the parfor parallel loop as defined here.

Matlabpool can be run on the Cheaha from the head node.

1. Login to the Cheaha head node with X using: ssh -X USERID@cheaha.uabgrid.uab.edu
3. Start Matlab in X using: matlab -c 27000@lmgr.uabgrid.uab.edu


This should open up a Matlab window on your Desktop. User needs to setup the Parallel Config and copy the required files to the user folder on the Cheaha. A similar process for the same on a desktop is mentioned here.

Validate the parallel configuration.

Open matlabpool from the MATLAB command window using: matlabpool open cheaha 'numberOfProcessors'.
Output: Starting matlabpool using the 'cheaha' configuration ... connected to 'numberOfProcessors' labs.
Run Matlab job as you would run it using a local configuration on your Desktop.
Close matlabpool using: matlabpool close all


## MATLAB Support / Mailing List

As with any application or computer language, learning to use MATLAB to analyze data or to develop or modify MATLAB applications is an individual responsibility. There is ample application documentation available from the Mathworks website, potential outreach to colleagues who also use MATLAB, and options for consultation with Mathworks. Mathworks also host on-campus training seminars several times a year and provides many on-line learning tutorials.

Installation support for MATLAB at UAB is provided by your local IT support organization and the Docs wiki.

### Mathworks Website

Your first and best option for application-specific questions on MATLAB is to refer to the on-line MATLAB documentation. The Mathworks site also provides a a support matrix and an on-line knowledge base.

### UAB MATLAB Wiki

The MATLAB page on the Docs wiki is the starting point for installing MATLAB at UAB and, optionally, configuring it to use cluster computing. All users are encouraged to contribute to the MATLAB knowledge in this wiki, especially if you see areas where improvements are needed. Remember, this knowledge base is only as good as the people who contribute to it.

Contributing to the wiki is as easy as clicking the login link on the top-right of the page and signing in with your UAB BlazerID. If you are unsure about making an edit, you can make suggestions for improvement on the page's Discussion tab or discuss the proposed improvement in the MATLAB user group.

### UAB MATLAB User Group

At UAB, MATLAB installation support is provided by your local IT support group. Support for application specific questions is available from peers in your research group. We realize that some people are not as familiar with MATLAB as others. For this reason, we have established a MATLAB user forum (mailing list) where users of MATLAB at UAB can help answer each others questions.

This is a network of volunteers sharing their knowledge with peers. You are encouraged to reach out to this community for questions on using MATLAB by

Archives of MATLAB user group discussions are available on-line at https://vo.uabgrid.uab.edu/sympa/arc/matlab-user. You may find your question is already answered in these archives.