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--- matlab_on_cluster [2016/06/03 07:45] – [Parallel Computing Toolbox aka matlabpool] 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 53: / Line 54: @@
 matlabpool close % release the resources
 </code>
-==== Gotchas ====
+===== Managing parallel configurations =====
+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.
+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
+  * `parfor' loops cannot be nested
 ===== Useful readings =====
 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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