matlab_usage
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matlab_usage [2016/03/04 22:16] mgstauff [Parallel Toolbox Considerations] |
matlab_usage [2018/02/06 20:44] (current) mgstauff [Matlab Search Path] |
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| If you need to replace the default CfN settings in your startup.m file, see / | If you need to replace the default CfN settings in your startup.m file, see / | ||
| + | ==== Matlab Search Path ==== | ||
| + | To customize the Matlab search path, change your ~/ | ||
| + | |||
| + | https:// | ||
| + | |||
| + | Add the definition to your ~/ | ||
| ==== Matlab via qsub batch jobs==== | ==== Matlab via qsub batch jobs==== | ||
| You may need to run Matlab scripts in a qsub job. It's fairly easy. This command will run a series of Matlab commands from the command line (shell), which we can use in a qsub job script: | You may need to run Matlab scripts in a qsub job. It's fairly easy. This command will run a series of Matlab commands from the command line (shell), which we can use in a qsub job script: | ||
| Line 38: | Line 44: | ||
| Matlab is known to be greedy about how many CPU cores it uses. When it sees, for example, 16 cores on the machine where it's running, it will generally use 16 threads for its own code that is multi-threaded. The cluster will automatically set the number of threads for matlab to use according to how many cores/slots you requested for your job. This is done in two ways: | Matlab is known to be greedy about how many CPU cores it uses. When it sees, for example, 16 cores on the machine where it's running, it will generally use 16 threads for its own code that is multi-threaded. The cluster will automatically set the number of threads for matlab to use according to how many cores/slots you requested for your job. This is done in two ways: | ||
| - | * Single core/slot: a wrapper around the ' | + | |
| - | * Multiple cores/ | + | |
| - | *WARNING* | + | **WARNING** |
| If you notice matlab running very slowly during heavy computation (e.g. much slower than when you prototyped on your own machine), it may be because matlab is using more threads than you have cores/slots assigned to your job. | If you notice matlab running very slowly during heavy computation (e.g. much slower than when you prototyped on your own machine), it may be because matlab is using more threads than you have cores/slots assigned to your job. | ||
| In this case, the slowdown happens because SGE ' | In this case, the slowdown happens because SGE ' | ||
| - | What to do: you should request more cores to lessen the computational bottleneck. Anecdotally, | + | What to do: you should request more cores to lessen the computational bottleneck. Anecdotally, |
| + | See more discussion in [[using_ogs_sge# | ||
| ==== Parallel Toolbox Considerations ==== | ==== Parallel Toolbox Considerations ==== | ||
| Line 54: | Line 61: | ||
| === Number of Workers === | === Number of Workers === | ||
| - | When using Matlab' | + | When using Matlab' |
| NOTE: Your jobs (qsub or qlogin) run on a single compute node for easier parallel processing, and each compute node has only 16 cores. So you don't want to ask for more than 16 slots (and thus matlab workers) for a job. But also note that asking for 16 slots meaning waiting for a compute node to be completely free before you can start your job. | NOTE: Your jobs (qsub or qlogin) run on a single compute node for easier parallel processing, and each compute node has only 16 cores. So you don't want to ask for more than 16 slots (and thus matlab workers) for a job. But also note that asking for 16 slots meaning waiting for a compute node to be completely free before you can start your job. | ||
matlab_usage.1457129808.txt.gz ยท Last modified: 2016/03/04 22:16 by mgstauff
