Mathworks MATLAB
MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language. Developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, and Fortran. (taken from http://en.wikipedia.org/wiki/MATLAB, more details there)
http://www.mathworks.de/products/matlab/
Versions
We currently offer the following MATLAB versions:
math/MATLAB/2017a math/MATLAB/2018b
You can query the versions yourself with module av |& grep -i matlab
.
Usage
Load the most recent version available with:
$ module load math/MATLAB
You can also load a particular version with module load math/MATLAB/<version>
, e.g. module load math/MATLAB/2017a
See the vendor documentation: https://www.mathworks.com/help/matlab/
License
Matlab | |
---|---|
Version: | R2017a, 2018b |
License: | University of Mainz |
Developer: | Mathworks |
Toolboxes
The currently available toolboxes are
Toolbox | Version |
---|---|
Curve Fitting Toolbox | 3.5.8 |
Econometrics Toolbox | 5.1 |
Fuzzy Logic Toolbox | 2.4 |
Image Acquisition Toolbox | 5.5 |
Image Processing Toolbox | 10.3 |
MATLAB Compiler | 7.0 |
MATLAB Compiler SDK | 6.6 |
Mapping Toolbox | 4.7 |
Optimization Toolbox | 8.2 |
Parallel Computing Toolbox | 6.13 |
Partial Differential Equation Toolbox | 3.1 |
Signal Processing Toolbox | 8.1 |
Statistics and Machine Learning Toolbox | 11.4 |
Symbolic Math Toolbox | 8.2 |
Wavelet Toolbox | 5.1 |
Using Matlab
Using Matlab is possible several ways, which we would like to briefly introduce here.
Interactive Job Submission
Request resources according to your needs, e.g. with:
[joe_user@login]$ srun -n<ntasks> -p<partition> -A<account> -t<time> --mem<amount> --pty --preserve-env $SHELL
Load the desired Matlab module:
module load math/MATLAB
Now you can run Matlab. Add -nojvm
flag to start Matlab without the Java virtual machine, nosplash
prevents Matlab from displaying the Matlab logo.
matlab -nodisplay -nosplash
Check the version info and the available toolboxes for that version:
>> ver
gives:
------------------------------------------------------------------------------------------- MATLAB Version: 9.5.0.944444 (R2018b) ... Operating System: Linux 3.10.0-957.5.1.el7.x86_64 #1 SMP Fri Feb 1 14:54:57 UTC 2019 x86_64 Java Version: Java is not enabled ------------------------------------------------------------------------------------------- MATLAB Version 9.5 (R2018b) Curve Fitting Toolbox Version 3.5.8 (R2018b) Econometrics Toolbox Version 5.1 (R2018b) ...
The use of the Matlab-Compiler is to be preferred!
Only a limited number of licences are available on the cluster. It is therefore preferable to use the Matlab-Compiler to compile your scripts beforehand. We explain more about the Matlab-Compiler as follows.Matlab-Compiler
There are several options to compile your Matlab code to stand-alone executables/libraries. Being independent of licenses is one of the major advantages here, of course. But when running compiled code with the Matlab Runtime Envirenment (MRE) on the cluster you have to consider the threading of your code just as well as when you run Matlab itself. Generally, Matlab detects the number of physical cores and opens the same amount of threads to make full use of the multithreading implemented in the built-in functions. So, if you call
mcc -m my_mfile.m
you obtain multithread code. Often this might be wanted, but you have to make sure that you select the appropriate resources for this then - namely, the appropriate core-affinity. Since Matlab wants to use everything on a host you'll have to call bsub -n 1 -R 'affinity[cores(64)]'
and an appropriate memory reservation.
On the other hand, if your code doesn't need the full multithreading capability, which often is the case, you should compile your code with the flag 'singleCompThread'
mcc -m -singleCompThread my_mfile.m
. This makes sure that your standalone code will run on a single computational thread, which not only doesn't frustrate the core scheduler and the other users less but improves performance of your code because less time is spent in scheduling all the threads on one core.
Examples
Submitting a Matlab job
The flag nojvm
starts Matlab without the Java virtual machine, nodisplay
instructs Matlab to run without the GUI, nosplash
prevents Matlab from displaying the Matlab logo and r
defines the name of the script you want to run.
Notice: Save your file with the .m
extension, but call it without the .m
extension.
For full nodes consider
#SBATCH -p nodeshort # Queue name #SBATCH -n 32 # Total number of tasks #SBATCH -c 2 # Total number of cores
as Matlab will not be able to fully utilize the node, but considers every FPU equal to a CPU.
Compiling a m-file on a node
Using the following shell script you can compile a m-file into a stand-alone c application. It's a variation of the script for using local scratch on a node.
- compileFile.sh
#!/bin/bash # Store working directory to be safe SAVEDPWD=`pwd` FILENAME=$1 # We define a bash function to do the cleaning when the signal is caught cleanup(){ cp /jobdir/${LSB_JOBID}/*$FILENAME.sh ${SAVEDPWD}/ cp /jobdir/${LSB_JOBID}/$FILENAME ${SAVEDPWD}/ exit 0 } # Register the cleanup function when SIGUSR2 is sent, ten minutes before the job gets killed trap 'cleanup' SIGUSR2 # Copy input file cp ${SAVEDPWD}/$FILENAME.m /jobdir/${LSB_JOBID}/ # Go to jobdir and start the program cd /jobdir/${LSB_JOBID} mcc -m $FILENAME.m # Call the cleanup function when everything went fine cleanup