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==== Note ====

You can also run matlab jobs via scripts like other software.

Create a file with the matlab commands and then create a shell script to submit the job.

It would look like

<code>

#!/bin/bash
# submit via 'bsub < run.serial'

#BSUB -q matlab

#BSUB -J test
#BSUB -o test.stdout
#BSUB -e test.stderr



matlab -no display < my_code.m > /dev/null

</code>

==== Matlab 2013a ====

Is now the default matlab version, just change the paths in scripts below
 --- //[[hmeij@wesleyan.edu|Meij, Henk]] 2013/03/14 14:57//

==== Matlab 2010b ====

So, now that 2010b is the version of Matlab and we're using Lava scheduler we need to integrate the two.

  * [[http://www.mathworks.com/support/solutions/en/data/1-4SUZLX/?solution=1-4SUZLX|How can I integrate MATLAB Distributed Computing Server with the Lava scheduler?]]
  * [[http://www.mathworks.com/products/distriben/supported/sched/|Scheduler Support in Parallel Computing Toolbox and MATLAB Distributed Computing Server]]
  * [[http://www.mathworks.com/help/toolbox/distcomp/bqur7ev-35.html|Part 1]]
  * [[http://www.mathworks.com/help/toolbox/distcomp/bqxceii-1.html|Part2]]

=== Serial 1 ===

In the example below, the code waits for the results.  Don't do that when submitting jobs, it is just for debugging purposes.

This old way still works for distributed jobs:

<code>

% distributed matlab jobs
% start 'matlab -nodisplay', issue the command 'Simple'

% set up the scheduler and matlab worker environment
sched = findResource('scheduler', 'type', 'generic');
set(sched, 'HasSharedFilesystem', true);
set(sched, 'ClusterMatlabRoot', '/share/apps/matlab/2010b')
set(sched, 'SubmitFcn', @lsfSimpleSubmitFcn)

% specify location for worker output
set(sched, 'DataLocation', '/home/hmeij/hp/matlab')

% create job and assign tasks to be done
j = createJob(sched);
T = createTask(j, @rand, 1, {{3,3} {3,3} {3,3} {3,3} {3,3}});

% submit job, wait for jobs to finish, fetch output
submit(j)

% WARNING: this may hang if the workers are busy!
waitForState(j)
results = getAllOutputArguments(j);
results{1:5}
% better to do it like Simple2.m


</code>

=== Serial 2 ===

After you submit the job, you can exit matlab.

<code>

% distributed matlab jobs
% start 'matlab -nodisplay', issue the command 'Simple2'

% set up the scheduler and matlab worker environment
sched = findResource('scheduler', 'type', 'generic');
set(sched, 'HasSharedFilesystem', true);
set(sched, 'ClusterMatlabRoot', '/share/apps/matlab/2010b')
set(sched, 'SubmitFcn', @lsfSimpleSubmitFcn)

% specify location for worker output
set(sched, 'DataLocation', '/home/hmeij/hp/matlab')

% create job and assign tasks to be done
j = createJob(sched);
T = createTask(j, @rand, 1, {{3,3} {3,3} {3,3} {3,3} {3,3}});

% submit job, then exit matlab interactive session
submit(j)
get(sched)

</code>

=== Parallel ===

Slightly different syntax.  Adjust your number of workers values based on some benchmarking, not always do the most workers finish a job in the shortest amount of time.

<code>

% parallel matlab jobs
% start 'matlab -nodisplay', issue the command 'Simplep'

% set up the scheduler and matlab worker environment
sched = findResource('scheduler', 'type', 'generic')
set(sched, 'HasSharedFilesystem', true);
set(sched, 'ClusterMatlabRoot', '/share/apps/matlab/2010b')
set(sched, 'ParallelSubmitFcn', @lsfParallelSubmitFcn)

% specify location for worker output
set(sched, 'DataLocation', '/home/hmeij/hp/matlab')
pj = createParallelJob(sched);
set(pj, 'MaximumNumberOfWorkers', 8)
set(pj, 'MinimumNumberOfWorkers', 8)
T = createTask(pj, @rand, 1, {{300,300}});

% submit job, wait to finish, get status jobs, gather results
submit(pj)
get(sched)
% you can now exit matlab
% at system prompt type 'bjobs'


</code>



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