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MATLAB can be used by loading its module. We highly recommend to choose a particular – better: the newest – version, e. g.:

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languagebash

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Supported Releases of MATLAB and MATLAB Compiler Runtime

R2019bloadmatlab/R2019b-genericmatlabmcrR2019b-genericR2019a_Update5matlab-R2019a

MATLAB Release (Patch level)

MATLAB Compiler Runtime

Comment
R2020a


Code Block
languagebash
> module 
remove 
Code Block
languagebash
intel-mpi
> module load 
intel-
mpi/
R2019brecommended versionR2019a (Update 5)
Code Block
languagebash
2018-intel
> module load matlab/
R2020a-generic



Code Block
languagebash
> module remove intel-mpi
> module load 
intel-mpi/2018-intel
> module load matlab-mcr/
R2020a-generic
R2019a

Trouble Loading MATLAB Module

The MATLAB module is not visible and, thus, cannot be loaded. Try to get access to the current software stack via following command. Then continue using "module avail" or "module load".

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R2020a


Warning

Using the default Intel-MPI module (Version 2019), unintended crashes of parallel MATLAB jobs might occur. Please switch to Intel MPI 2018.


R2019b
(Update 5)


Code Block
languagebash
> module 

...

load 

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matlab/R2019b_Update5-generic



Code Block
languagebash
> module 

...

load matlab-

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mcr/R2019b-generic


R2019brecommended version
R2019a
(Update 7)


Code Block
languagebash
> module load matlab/R2019a_Update7-generic



Code Block
languagebash
> module load matlab-mcr/R2019a-generic


R2019a

Trouble Loading MATLAB Module

Warning
iconfalse
titleThe MATLAB module is not visible and cannot be loaded

Check your module environment by listing currently loaded modules. As part of LRZ software stack MATLAB is provided via Spack. A Spack module should be loaded. If not, check for available Spack modules and load the newest module.
In order to get access to the list of supported MATLAB releases, you have to load the Spack module spack/release/20.1.

Code Block
languagebash
> module list                       # list loaded modules
> module avail spack/release        # show available Spack modules
> module switch spack/release/20.1  # load Spack (example)
> module avail matlab               # check for MATLAB



Note
titleFall back to old MATLAB installation

You may also load old installations of MATLAB via an old Spack module. This might be helpful for particular use cases. But, this is a fallback solution! Old software stacks are not supported anymore! Some MATLAB features might not work because

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setup of MATLAB installation does not match updated system configurations, among others.


Useful MATLAB Commands

Run MATLAB via the "matlab" command only or add command-line arguments. Please consider: All MATLAB commandline command-line arguments are case-sensitive!

Start MATLAB GUI:

Code Block
languagebash
> matlab arg_1 ... arg_N


Command-line argumentMeaning
no argumentStart MATLAB GUI.
-nodesktop
Start MATLAB without desktop but allow GUI and graphics output

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languagebash

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.
-nodisplay
Start MATLAB without any GUI support

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languagebash

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.
-singleCompThread

Some intrinsic MATLAB functions automatically exploit multithreading. MATLAB can be forced to disable this feature

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languagebash

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.


Warning

Use this option for any work on the login nodes!


-r myfunc
Run a MATLAB script or function, e. g. myfunc.m

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Code Block
languagebash
> matlab -r myfunc
.

Interactive MATLAB Jobs in a Nutshell – the Convenient Way

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Usecases

Depending on the purpose, there are different possibilities to use MATLAB interactively:

  • MATLAB computations with focus on visualisation: We recommend to use our Remote Visualisation System.
  • Pure MATLAB computations: Interactive MATLAB sessions may be started on compute nodes of CoolMUC-2 or CoolMUC-3 by employing interactive Slurm jobs (see Slurm documentation).

Constraints

  • Interactive jobs depend on the availability of compute resources. Matlab may not start immediately.
  • Matlab will run on 1 compute node.
  • The time limit is set to 2 hours (= maximum time for interactive Slurm sessions).

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Slurm job scriptMatlab script

Serial batch job

Warning

No parallelization at all, MATLAB is intended to run on a single core.
Please use the "serial" cluster of the Linux Cluster!



Code Block
languagebash
titlematmul_serial.slurm
linenumberstrue
collapsetrue
#!/bin/bash
#SBATCH -o ./out/matlab_job.%j.%N.out
#SBATCH -e ./out/matlab_job.%j.%N.err
#SBATCH -D ./
#SBATCH -J matlab_serial_batch_job
#SBATCH --get-user-env
#SBATCH --export=NONE
#SBATCH --clusters=serial
#SBATCH --partition=serial_std
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --cpus-per-task=1
#SBATCH --mem=10000
#SBATCH --time=0:30:00
# As needed, remove/adjust memory requirement "--mem" in MB

module load slurm_setup
module load matlab/R2019b_Update5-generic

# Example: matrix-matrix multiplication C = A*B
#          with A of size NROWA x NCOLA and
#          B of size NROWB x NCOLB
NROWA=1000
NCOLA=2000
NROWB=2000
NCOLB=5000

# Run MATLAB
# => Using option -r don't add file extension .m to the function call!
# => MATLAB commandline arguments are case-sensitive!
matlab -nodisplay -singleCompThread \
       -r "matmul_serial([$NROWA $NCOLA], [$NROWB $NCOLB]);"



Code Block
languagetext
titlematmul_serial.m
linenumberstrue
collapsetrue
function [C, comptime] = matmul_serial(size_A, size_B)

%===============================================================================
% MATLAB EXAMPLE: SERIAL HELLO WORLD
%                 -> matrix-matrix multiplication C = A*B
%
% INPUT
%   size_A, size_B ... 2-element row vectors defining sizes of A and B
% OUTPUT
%   C ................ result
%   comptime ......... computation time (matrix product only)
%===============================================================================

%===============================================================================
% Check input
%===============================================================================
if nargin~=2
    error('Invalid number of input arguments!');
end
if size_A(2)~=size_B(1)
    error(sprintf('Dimension mismatch of A (%d columns) and B (%d rows)!',...
                  size_A(2), size_B(1)));
end

%===============================================================================
% Work
%===============================================================================
% Hello message from compute node
fprintf('Hello from MATLAB process PID=%d running on node %s!\n',...
        feature('getpid'),...
        strtrim(evalc('system(''hostname'');')));

% generate well-defined matrices
NA = prod(size_A);
NB = prod(size_B);
A = reshape( linspace( 1,NA, NA), size_A );
B = reshape( linspace(NB, 1, NB), size_B );

% compute
tic;
C = A*B;
comptime = toc;
fprintf('serial computation of matrix-matrix product:\n');
fprintf('\ttime = %.2f s\n', comptime);


Parallel job using multithreading

Warning

MATLAB will run on a single compute node.
Please use the partition "cm2_tiny" in cluster "cm2_tiny"!



Code Block
languagebash
titlematmul_mthread.slurm
linenumberstrue
collapsetrue
#!/bin/bash
#SBATCH -o ./out/matlab_job.%j.%N.out
#SBATCH -e ./out/matlab_job.%j.%N.err
#SBATCH -D ./
#SBATCH -J matlab_threading_batch_job
#SBATCH --get-user-env
#SBATCH --export=NONE
#SBATCH --clusters=cm2_tiny
#SBATCH --partition=cm2_tiny
#SBATCH --nodes=1
#SBATCH --tasks-per-node=1
#SBATCH --cpus-per-task=14
#SBATCH --time=00:30:00

module load slurm_setup
module load matlab/R2019b_Update5-generic

# Example: matrix-matrix multiplication C = A*B
#          with A of size NROWA x NCOLA and
#          B of size NROWB x NCOLB
NROWA=1000
NCOLA=2000
NROWB=2000
NCOLB=5000

# Run MATLAB
# => Using option -r don't add file extension .m to the function call!
# => MATLAB commandline arguments are case-sensitive!
matlab -nodisplay \
       -r "matmul_mthread([$NROWA $NCOLA], [$NROWB $NCOLB]);"



Code Block
languagetext
titlematmul_mthread.m
linenumberstrue
collapsetrue
function [C, comptime] = parallel_mthread(size_A, size_B)

%===============================================================================
% MATLAB EXAMPLE: PARALLEL HELLO WORLD USING MULTITHREADING
%                 -> matrix-matrix multiplication C = A*B
%
% INPUT
%   size_A, size_B ... 2-element row vectors defining sizes of A and B
% OUTPUT
%   C ................ result
%   comptime ......... computation time (matrix product only)
%===============================================================================

%===============================================================================
% Check input
%===============================================================================
if nargin~=2
    error('Invalid number of input arguments!');
end
if size_A(2)~=size_B(1)
    error(sprintf('Dimension mismatch of A (%d columns) and B (%d rows)!',...
                  size_A(2), size_B(1)));
end

%===============================================================================
% Manage multithreading
%===============================================================================
% Get number of threads depending on job type (batch job or interactive job).
% In batch jobs 1 MATLAB task will use "nw" threads. 
%
% obtain number of threads from Slurm environment variables
cluster = getenv('SLURM_CLUSTER_NAME');
if strcmp(cluster, 'inter')
    % interactive job
    nw = str2num(getenv('SLURM_JOB_CPUS_PER_NODE'));
elseif strcmp(cluster, 'cm2_tiny') || ...
       strcmp(cluster, 'mpp3') || ...
       strcmp(cluster, 'ivymuc')
    % batch job
    nw = str2num(getenv('SLURM_CPUS_PER_TASK'));
else
    % default
    nw = 1;
end
% set threads
maxNumCompThreads(nw);

%===============================================================================
% Work
%===============================================================================
fprintf('Hello from MATLAB process PID=%d running on node %s!\n',...
        feature('getpid'),...
        strtrim(evalc('system(''hostname'');')));

% generate well-defined matrices
NA = prod(size_A);
NB = prod(size_B);
A = reshape( linspace( 1,NA, NA), size_A );
B = reshape( linspace(NB, 1, NB), size_B );

% compute
tic;
C = A*B;
comptime = toc;
fprintf('parallel computation (multithreading) of matrix-matrix product:\n');
fprintf('\tnumber of threads = %d\n', nw);
fprintf('\ttime = %.2f s\n', comptime);


Parallel batch job using Parallel Computing Toolbox (PCT)

Warning

MATLAB will run on a single compute node.
Please use the partition "cm2_tiny" in cluster "cm2_tiny"!



Code Block
languagebash
titlematmul_pct.slurm
linenumberstrue
collapsetrue
#!/bin/bash
#SBATCH -o ./out/matlab_job.%j.%N.out
#SBATCH -e ./out/matlab_job.%j.%N.err
#SBATCH -D ./
#SBATCH -J matlab_pct_batch_job
#SBATCH --get-user-env
#SBATCH --export=NONE
#SBATCH --clusters=cm2_tiny
#SBATCH --partition=cm2_tiny
#SBATCH --nodes=1
#SBATCH --tasks-per-node=4
#SBATCH --cpus-per-task=1
#SBATCH --time=00:30:00

# IMPORTANT
# Default settings of Intel MPI module may disrupt 
# functionality of Parallel-Computing-Toolbox!
# Do one of the following solutions:  
# (1) Unload module mpi.intel:
module rm mpi.intel
# (2) If Intel MPI module is mandatory, add next line
# export KMP_AFFINITY=granularity=thread,none

module load slurm_setup
module load matlab/R2019b_Update5-generic

# Example: matrix-matrix multiplication C = A*B
#          with A of size NROWA x NCOLA and
#          B of size NROWB x NCOLB
NROWA=1000
NCOLA=2000
NROWB=2000
NCOLB=5000

# Run MATLAB
# => Using option -r don't add file extension .m to the function call!
# => MATLAB commandline arguments are case-sensitive!
matlab -nodisplay -singleCompThread \
       -r "matmul_pct([$NROWA $NCOLA], [$NROWB $NCOLB]);"


Code Block
languagetext
titlematmul_pct.m
linenumberstrue
collapsetrue
function [Cglob, comptime] = matmul_pct(size_A, size_B)

%===============================================================================
% MATLAB EXAMPLE: PARALLEL HELLO WORLD USING PCT TOOLBOX
%                 -> matrix-matrix multiplication C = A*B
%
% INPUT
%   size_A, size_B ... 2-element row vectors defining sizes of A and B
% OUTPUT
%   C ................ result
%   comptime ......... computation time (matrix product only)
%===============================================================================

%===============================================================================
% Check input
%===============================================================================
if nargin~=2
    error('Invalid number of input arguments!');
end
if size_A(2)~=size_B(1)
    error(sprintf('Dimension mismatch of A (%d columns) and B (%d rows)!',...
                  size_A(2), size_B(1)));
end

%===============================================================================
% Verify that no parallel pool is initialized by creating/deleting a dummy pool
%===============================================================================
if ~isempty(gcp('nocreate'))
    poolobj = gcp('nocreate');
    delete(poolobj);
end

%===============================================================================
% Start parallel pool
%===============================================================================
% Get number of workers depending on job type. Start parallel pool via "local"
% cluster object.
%
% obtain number of tasks from Slurm environment variables
cluster = getenv('SLURM_CLUSTER_NAME');
if strcmp(cluster, 'inter')
    % interactive job
    nw = str2num(getenv('SLURM_JOB_CPUS_PER_NODE'));
elseif strcmp(cluster, 'cm2_tiny') || ...
       strcmp(cluster, 'serial') || ...
       strcmp(cluster, 'mpp3') || ...
       strcmp(cluster, 'ivymuc')
    % batch job
    nw = str2num(getenv('SLURM_NTASKS'));
else
    % default
    nw = 1;
end

% disallow Threading
if maxNumCompThreads > 1
    maxNumCompThreads(1);
    warning('MultiThreading: number of threads has been set to 1!');
end

% create a local cluster object
pc = parcluster('local');
% set number of workers
pc.NumWorkers = nw;
% set the JobStorageLocation to SCRATCH (default: HOME -> not recommended)
pc.JobStorageLocation = strcat(getenv('SCRATCH'));
% start the parallel pool
poolobj = parpool(pc, nw);

%===============================================================================
% Work
%===============================================================================
spmd
    fprintf('Hello from MATLAB process PID=%d running on node %s!\n',...
            feature('getpid'),...
            getenv('HOSTNAME'));
end

% generate well-defined matrices
NA = prod(size_A);
NB = prod(size_B);
A = reshape( linspace( 1,NA, NA), size_A );
B = reshape( linspace(NB, 1, NB), size_B );

% distribute data to workers and do parallel computation
spmd
    Aloc = codistributed(A, codistributor2dbc([nw 1]));
    Bloc = codistributed(B, codistributor2dbc([1 nw]));
    tic;
    Cloc = Aloc*Bloc;
    t = toc;
end

comptime = max(cell2mat(t(:)));
fprintf('parallel computation (MPI) of matrix-matrix product:\n');
fprintf('\tnumber of tasks (MATLAB workers) = %d\n', nw);
fprintf('\ttime = %.2f s\n', comptime);

Cglob = gather(Cloc);

%===============================================================================
% Close parallel pool
%===============================================================================
delete(poolobj);

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