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matlab_on_cluster [2018/02/22 13:21] – [Matlab on multi-processor machines] lenocil | matlab_on_cluster [2021/06/24 07:19] (current) – [Matlab on multi-processor machines] lenocil | ||
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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 '' | 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 '' | ||
- | :!: Currently matlab2017a | + | |matlab |
- | + | |Before trying to parallelize any codes, please make sure your code works as expected on one processor.| | |
- | :!: 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.| |
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- | :!: matlab versions prior to 2007 do not have the features discussed here. | + | |
===== Parallel Computing Toolbox aka matlabpool ===== | ===== Parallel Computing Toolbox aka matlabpool ===== | ||
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matlabpool can be used to parallelize your m script across multiple cores in a single machine. | 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 |
< | < | ||
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- | DataLocation : /home/lenocil/ | + | DataLocation : /home/xxxxx/ |
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In matlab2010 the max number of workers is set to 8 where as that limit ip brought to 12 in matlab R2011b. | 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 | + | 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:// |
- | (you can buy it through our procurement office, email '' | + | and you will also need to create a `scheduler' |
To modify the local configuration | To modify the local configuration |