• Created by Unknown User (i.spisso@cineca.it), last modified on Jun 05, 2017

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 32 Next »

(last updated: )

In this page:


 

The following guide describe how to load, configure and use matlab @ CINECA's cluster 

Load the MATLAB module 

login to Galileo cluster, and type

[user@node166 ~]$ module load profile/eng autoload matlab/r2017a

Configuration

Configure MATLAB to submit jobs will by default to the cluster rather than submit to the local node or local machine.

Cluster Configuration

Start MATLAB, without desktop.

[user@node166 ~]$ matlab -nodesktop

 Configure MATLAB to run parallel jobs on your cluster by calling configCluster.  For each cluster, configCluster only needs to be called once per version of MATLAB, and once per user. 

>> configCluster

Local Configuration

After having installed MATLAB to your workstation 

Configuring Jobs

Prior to submitting the job, various parameters have to be specified in order to be passed to jobs, such as queue, username, e-mail, etc. 

NOTE:  Any parameters specified using the below workflow will be persistent between MATLAB sessions.

Before specifying any parameters, you will need to obtain a handle to the cluster object.

>> % Get a handle to the cluster
 >> c = parcluster;

 

You are required to specify an Account Name prior to submitting a job. You can retrieve your Account Name / Bugdet info by using the saldo command

>> % Specify an Account to use for MATLAB jobs
>> c.AdditionalProperties.AccountName = ‘account_name’

 

You can specify other additional parameters along with your job.

>> % Specify a queue to use for MATLAB jobs
>> c.AdditionalProperties.QueueName = ‘shared’
>> % Specify e-mail address to receive notifications about your job
>> c.AdditionalProperties.EmailAddress = ‘test@foo.com’
>> % Specify the walltime
>> c.AdditionalProperties.WallTime = '00:10:00'

>> % Specify processor cores per node.  Default is 16.

>> c.AdditionalProperties.ProcsPerNode = 16

>> % Turn on the Debug Message.  Default is off (logical 0).

>> c.AdditionalProperties.DebugMessagesTurnedOn = 1

 

To see the values of the current configuration options, call the specific AdditionalProperties name.

>> % To view current configurations
>> c.AdditionalProperties.QueueName

 

Or to see the entire configuration

>> c.AdditionalProperties

 

To clear a value, assign the property an empty value (‘’, [], or false).

>> % To clear a configuration that takes a string as input 
 >> c.AdditionalProperties.EmailAddress = ‘ ’

 

To save a profile, with your configuration ....

Serial Jobs

Use the batch command to submit asynchronous jobs to the cluster.  The batch command will return a job object which is used to access the output of the submitted job.  See the MATLAB documentation for more help on batch.

>> % Get a handle to the cluster
 >> c = parcluster;

 

>> % Submit job to query where MATLAB is running on the cluster

>> j = c.batch(@pwd, 1, {});

 

>> % Query job for state:  queued | running | finished 

>> j.State

 

>> % If state is finished, fetch results

>> j.fetchOutputs{:}

 

>> % Delete the job after results are no longer needed

>> j.delete

 

To retrieve a list of currently running or completed jobs, call parcluster to retrieve the cluster object.  The cluster object stores an array of jobs that were run, are running, or are queued to run.  This allows us to fetch the results of completed jobs.  Retrieve and view the list of jobs as shown below.

>> c = parcluster;
>> jobs = c.Jobs

 

Once we’ve identified the job we want, we can retrieve the results as we’ve done previously.

fetchOutputs is used to retrieve function output arguments; if using batch with a script, use load instead.   Data that has been written to files on the cluster needs be retrieved directly from the file system.

 

To view results of a previously completed job:

>> % Get a handle on job with job array index 2 (2x1)j
>> j2 = c.Jobs(2);

 

NOTE: You can view a list of your jobs, as well as their IDs, using the above c.Jobs command. 

>> % Fetch results for job with ID 2
>> j2.fetchOutputs{:}

 

>> % If the job produces an error view the error log file
>> c.getDebugLog(j.Tasks(1))

Parallel Jobs

Debugging

To learn More

Parallel Computing Benchmarck

Checking the license server

To check the license server status, please type: 

[user@node165 ispisso0]$ module load profile/eng autoload matlab/r2017a
[user@node165 ispisso0]$ lmutil lmstat -a -c $MLM_LICENSE_FILE

Feature enabled: 

Users of MATLAB:  5 licenses issued

Users of Distrib_Computing_Toolbox:  5 licenses issued

Users of MATLAB_Distrib_Comp_Engine:  32 licenses issued

To use Matlab, you have to be added to the unix group cin_matlab. Please ask for authorization to superc@cineca.it


 

 

dependences:

 outgoing links:

  • No labels