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--- matlab_on_cluster [2016/06/03 09:20] – [Managing parallel configurations] lenocil
+++ matlab_on_cluster [2021/06/24 07:19] (current) – [Matlab on multi-processor machines] lenocil
@@ Line 1: / Line 1: @@
 ====== Matlab on multi-processor machines ======
-The aim of this short guide is to get you started with using matlab in a multi-processor environment. The goal is to instruct matlab to use a `pool' of ''n'' processors rather than a single one to speed up calculations.
-:!: Before trying to parallelize any codes, please make sure your code works as expected on one processor.
+The aim of this short guide is to get you started with using matlab in a multi-processor environment. The goal is to instruct matlab to use a `pool' of ''n'' processors rather than a single one to speed up calculations.
-:!: matlab versions prior to 2007 do not have the features discussed here.
+|matlab is available on all Lorentz Institute and Sterrewacht cluster machines.|
+|Before trying to parallelize any codes, please make sure your code works as expected on one processor.|
+|matlab versions prior to 2007 do not have the features discussed here.|
 =====  Parallel Computing Toolbox aka matlabpool =====
@@ Line 10: / Line 11: @@
 matlabpool can be used to parallelize your m script across multiple cores in a single machine.
-Open matlab and initialize the parallel environment
+Open matlab ((Type ''ml spider matlab'' to list available versions)) and initialize the parallel environment
 <code>
@@ Line 27: / Line 28: @@
              ClusterOsType : unix
                ClusterSize : 8
-              DataLocation : /home/lenocil/.matlab/local_scheduler_data/R2010b
+              DataLocation : /home/xxxxx/.matlab/local_scheduler_data/R2010b
        HasSharedFilesystem : true
@@ Line 54: / Line 55: @@
 </code>
 ===== Managing parallel configurations =====
-The `local' configuration is the default. Unfortunately this configuration imposes limits on the numbers of workers available to the Parallel Computing Toolbox and no Matlab Distributed Computing Server (MDCS).
+The `local' configuration is the default. Unfortunately this configuration imposes limits on the numbers of workers available to the matlabpool aka Parallel Computing Toolbox and no Matlab Distributed Computing Server (MDCS) installed.
 In matlab2010 the max number of workers is set to 8 where as that limit ip brought to 12 in matlab R2011b.
-==== Gotchas ====
+If you wanted to use 64 workers (for instance on one of the maris nodes), you will need a 64-node MDCS licence ((Leiden University has an unlimited access license for everybody, see https://nl.mathworks.com/academia/tah-portal/universiteit-leiden-31485292.html))
+ and you will also need to create a `scheduler' to manage these resources. There are detailed instructions on how to do this at http://nl.mathworks.com/support/product/DM/installation/ver_current/.
+To modify the local configuration
+<code>
+jm=findResource('scheduler', 'configuration', 'local');
+jm.ClusterSize=6
+jm.DataLocation="/somewhere/you/like"
+</code>
+To check what configurations are available and which one is loaded use
+<code>
+[conf, allConf] = defaultParallelConfig
+conf =
+test
+allConf =
+    'local'    'test'
+</code>
+===== Gotchas =====
   * `parfor' executes loop in an order that suits matlab, that is not sequentially
   * `parfor' loops cannot be nested
@@ Line 64: / Line 91: @@
 http://vtchl.uiuc.edu/sites/default/files/MATLAB_Report.pdf
+http://www.mathworks.com/support/product/DM/installation/ver_current/Files/mdcs-mjs-quickstart-guide.pdf
+http://nl.mathworks.com/help/distcomp/program-independent-jobs-for-a-generic-scheduler.html

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