# Matlab on Caviness

For use on Caviness, MATLAB projects should be developed using a Desktop installation of MATLAB and then copied to Caviness to be run in batch. Here an extended MATLAB example is considered involving one simple MATLAB function, and two MATLAB scripts to execute this function in a loop, and another to execute in parallel using the Parallel Computing Toolbox.

Details on how to run these two scripts in batch are given with the resulting output files. There is also a section with UNIX commands you can use to watch your jobs and gather timing and core count numbers. It is important to know how much memory will be needed and how many cores will be used to set your resource requirements. If you do not ask for enough memory your job will fail. If you do not ask for enough cores, the job will take longer.

Even though it easier to develop on a desktop, MATLAB can be run interactively on Caviness, however it is not recommended for scripts that are long and computationally intensive.
Two interactive jobs are demonstrated. One shows how to test the function by executing the function one time. A
second example shows an interactive session, which starts multiple MATLAB pool of workers to execute the function in a loop using the Parallel Computing toolbox command, ** parfor**.
The Parallel Computing toolbox gives a faster time to completion, but more memory and CPU resources are consumed.

You can run MATLAB as a Desktop GUI application on Caviness, but again this is not recommended as the graphics are slow to display especially with a lower bandwidth network connection.

Many MATLAB research projects fall in the “high throughput computing” category. One run can be done on the desktop, but it is desired complete 100s or 1000s of independent runs. This greatly increases disk, memory and CPU requirements. Thus we have a final example that gives the recommended workflow to scale your job to multiple nodes. Compile the MATLAB code with single thread option and deploy the job as an grid engine array job.

# Getting Started

There will be several examples covered in the following sections. To help make things easier to following it is suggested to make a new directory in your home directory ` ~/ `

or in your workgroup directory ` $WORKDIR `

. Then `cd`

into the directory. In the new directory, you can add the maxEig.m and script.m files. These two files will be used in several of the examples.

[traine@login00 ~]$ mkdir matlab_example [traine@login00 ~]$ cd matlab_example

**Example Directories**

As you go through the following example it is suggested that you also create a new directory, for each of them. It will help make it easier to follow and track output files of the different jobs that you will be running.

Now create the following file and put it in the `~/matlab_example`

directory

## Matlab function

We will be using this sample function on the Caviness cluster in multiple demonstrations.

- maxEig.m
function maxe = maxEig(sd,dim) % maxEig maximum real eigenvalue of a normally distributed random matrix % Input parameters % sd - seed for random generator % dim - size of the square matrix % Output value % maxe - maximum real eigenvalue if (isdeployed) sd = str2num(sd) dim = str2num(dim) end rng(sd); ev = eig( randn(dim) ); maxe = max( ev(imag(ev)==0) ) end

The remainder of this page is based on using this MATLAB function to illustrate using MATLAB interactively and batch. The function will be executed interactively on multiple cores using multiple computational threads, and with 12 workers from a MATLAB pool. A MATLAB script with be run in batch to loop with multiple computational threads again using a MATLAB pool.

Finally it will be compiled and deployed using the MATLAB Compiler Runtime (MCR) environment.

`isreal`

, but it is useless to select real values from a complex array, since it will return false for all the elements of a complex array. Thus we use the selecting reals by the property that their imaginary part is 0.0. This may be subject to round-off errors, both by selecting complex numbers with very small imaginary parts, or by not selecting some real eigenvalues where the imaginary part is non-zero from rounding.
maxe = max( ev(imag(ev)==0) ); fprintf('sd=%d counte=%d maxe=%.4f\n', sd, length(ev(imag(ev)==0)), maxe)

### Matlab script

Now, write a MATLAB script file and put it in the `~/matlab_example`

directory. It should have a comment on the first line describing the purpose of the script and have the `quit`

command on the last line. This script will call the maxEig function 200 times and report the average:

- script.m
% script to run maxEig function 200 times and print average. count = 200; dim = 5001; sumMaxe = 0; tic; for i=1:count; sumMaxe = sumMaxe + maxEig(i,dim); end; toc avgMaxEig = sumMaxe/count quit

This is a detailed script example, which calls the `maxEig`

function. This example does no file I/O, all the I/O is to standard out. In MATLAB, assignments, not terminated by a semicolon, are displayed on the screen (standard out in batch).

**command (equivalent to MATLAB**

*quit***). This is meant to be a complete script, which terminates MATLAB when done. If you run this from the bash command line (interactively) with the**

*exit*`-r script`

option, it will come back with a bash prompt when completed. If this is run from a batch job, then you can do other commands in your batch script after the MATLAB script completes.
Without the ** quit** you will come back to the MATLAB prompt on completion for a interactive job. If this is the last line of a batch queue script, then the only difference will be the MATLAB prompt

`»`

at the very end of the output file. MATLAB treats the end of batch script file the same as exiting the window, which is the preferred way to exit the MATLAB GUI.
## Copy the project folder

If you created the files on your desktop version of MATLAB, now copy the folder to your `~/matlab_example`

project directory on the cluster.
Use any file transfer client to copy your project directory.

# Batch Job

You should have a copy of your MATLAB project directory on the cluster.

**Versions of MATLAB**

MATLAB has a new version twice a year. It is important to keep the version you use on your desktop the same as the one on the cluster. The command

vpkg_versions matlab

will show you the versions available on a cluster. Choose the one that matches the version on your desktop. We recommend you do not upgrade MATLAB in the middle of a project, unless there is a new feature or bug fix you need.

**Two directories**

It is frequently advisable to keep your MATLAB project clean from non-MATLAB files such as the job script file and the script output file. But you may combine them, and even use the MATLAB editor to create the script file and look at the output file. If you create the file on a Windows desktop, take care to not transfer the files as binary. See Transferring Files to/from Caviness for details.

When you have one combined directory, do not put the `cd`

command in the queue script; instead, change
to the project directory using `cd`

on the command line, before submitting your job.

## Create a job script file

You should create a job script file to submit a batch job. Start by modifying a batch job script template file (`/opt/shared/templates/slurm/generic/serial.qs`

), for example, to submit a serial job using one core on a compute node,
In your newly copied serial.qs file, add the following lines at the end.

[traine@login00 matlab_example]$ cp /opt/shared/templates/slurm/generic/serial.qs matlab_first.qs

# Add vpkg_require commands after this line: vpkg_require matlab #Running the Matlab main_script matlab -nodisplay -singleCompThread -batch main_script

Note we did not specify a version of MATLAB with the VALET command, so we will get the default version (`*`

) defined in VALET. This is okay for our examples, but in practice and reproducibility of your jobs, you should specify a MATLAB version. Now make a new file call `main_script.m`

Add the below lines to the file.

display 'Hello World'

When this script runs it will display ` Hello World `

.

## Submit batch job

Your shell must be in a workgroup environment
to submit any jobs.
Use the `sbatch`

command to submit a batch job
and note the `«JOBID»`

that is assigned to your job. For example, if your job script file name is `matlab_first.qs`

, then to
submit the job you would type

sbatch matlab_first.qs

**WARNING: Please choose a workgroup before submitting jobs**

This is the message you get if you are not in a workgroup.

sbatch: error: Batch job submission failed: Invalid account or account/partition combination specified

**Bash script vs job script**

It is true that a job script file is (usually) a bash script, but it must be executed with the `sbatch`

command instead of the `sh`

command. This way it is process by the job scheduler, Slurm, and the appropiate Slurm commands will allocate the requested resources and the job will be run on a compute node.

## Wait for job to complete

You can check on the status of you job with the `scontrol show job`

command.
For example, to list the information for job `«JOBID»`

, type

scontrol show job <<JOBID>>

For long running jobs, you could change your job script to notify you via an email message when the job is complete.

## Post process job

All MATLAB output data files will be in the project directory, but the MATLAB standard output will be in
the current directory, from which you submitted the job. If you did not redefine Slurm output for your job, then you'll be looking for a file `slurm-«JOBID».out`

.

# Interactive job

Here are specific details for running MATLAB as an interactive job on a compute node. You should have a copy of your MATLAB project directory on the cluster and will be referred to a `project_directory`

in the examples below.

## Command-line

You should work on a compute node when in command-line MATLAB.
Your shell must be in a workgroup environment
to submit a single threaded interactive job using `salloc`

.

[traine@login00 ~]$ workgroup -g it_css [(it_css:traine)@login00 ~]$ salloc --partition=_workgroup_ salloc: Pending job allocation 7809686 salloc: job 7809686 queued and waiting for resources salloc: job 7809686 has been allocated resources salloc: Granted job allocation 7809686 salloc: Waiting for resource configuration salloc: Nodes r00n16 are ready for job [traine@r00n16 ~]$ vpkg_require matlab Adding package `matlab/r2018b` to your environment [traine@r00n16 ~]$ cd matlab_example [traine@r00n16 matlab_example]$ matlab -nodesktop -singleCompThread MATLAB is selecting SOFTWARE OPENGL rendering. < M A T L A B (R) > Copyright 1984-2018 The MathWorks, Inc. R2018b (9.5.0.944444) 64-bit (glnxa64) August 28, 2018 To get started, type doc. For product information, visit www.mathworks.com. >>

This will start a interactive command-line session in your terminal window. When done type the `quit`

or `exit`

to terminated the MATLAB session and then `exit`

to terminated the salloc session. Again note, a specific version of MATLAB was not specified, so at the time of writing this wiki page the default version defined in VALET was version 2018b.

MATLAB is selecting SOFTWARE OPENGL rendering. < M A T L A B (R) > Copyright 1984-2018 The MathWorks, Inc. R2018b (9.5.0.944444) 64-bit (glnxa64) August 28, 2018 To get started, type doc. For product information, visit www.mathworks.com. >>quit [traine@r00n16 matlab_example]$ exit exit salloc: Relinquishing job allocation 7809686 [(it_css:traine)@login00 ~]$

## Desktop

You should be on a compute node before you start MATLAB. To start a MATLAB desktop (GUI mode) on a cluster, you must be running an X11 server and you must have connected to the cluster with `ssh`

using X11 tunneling.

You must be in a workgroup environment to submit a job using `salloc`

.

[traine@login00 ~]$ workgroup -g it_css [(it_css:traine)@login00 ~]$ salloc --x11 -N1 -n1 --partition=_workgroup_ salloc: Pending job allocation 7790913 salloc: job 7790913 queued and waiting for resources salloc: job 7790913 has been allocated resources salloc: Granted job allocation 7790913 salloc: Waiting for resource configuration salloc: Nodes r00n10 are ready for job [traine@r00n10 ~]$ vpkg_require matlab Adding package `matlab/r2018b` to your environment [traine@r00n10 ~]$ matlab MATLAB is selecting SOFTWARE OPENGL rendering.

This will start an interactive MATLAB desktop GUI mode session on your desktop in an X11 window using your workgroup resources.

When done type the `quit`

or `exit`

in the command window or just close the window. When back at the terminal bash prompt, type `exit`

to terminate the `salloc`

interactive session and return to the login (head) node.

See tips on starting MATLAB in an interactive session without the desktop, including executing a script.

For more information, review the instructions for setting up X11 connections with an SSH connection for Windows, Mac, and Linux OS.

For more information on GUI Applications on Caviness, visit Launching GUI Applications (X11 Forwarding).

# Compiling with Matlab

We show the three most common ways to work with compilers when using MATLAB.

- Compiling your Matlab code to run in the MCR (MATLAB Compiler Runtime)
- Compiling your C or Fortran program to call MATLAB engine.
- Compiling your own function in C or Fortran to be used in a MATLAB session.

Warning: You are using gcc version '4.9.3'. The version currently supported with MEX is '4.7.x'. For a list of currently supported compilers see: http://www.mathworks.com/support/compilers/current_release.

But the compilation completes successfully.

## Compiling your Matlab code

There is an example MCR project in the `/opt/shared/templates/`

directory for you to copy and try. Copy on the head node and use `salloc`

to compile with MATLAB on the `devel`

partition (.i.e max request time on the `devel`

partition is 2 hours and 4 cores). Once your program is compiled, you can run it interactively or batch, without needing a MATLAB license.

### Copy dev-projects template

On the head node, copy the example project into your current directory using the following commands

[traine@login00 ~]$ workgroup -g it_css [(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ cp -r /opt/shared/templates/dev-projects/Projects/MCR . [(it_css:traine)@login00 matlab_example]$ cd MCR

### Compile with make

Now compile on the compute node by using

[(it_css:traine)@login00 MCR]$ salloc --partition=devel salloc: Granted job allocation 7861739 salloc: Waiting for resource configuration salloc: Nodes r00n56 are ready for job [triane@r00n56 MCR]$

`salloc`

. The prompt (`[(it_css:traine)@login00 MCR]$`

) displays the workgroup (e.g. `it_css`

) in this example. Also in this example specifying no other options, our job will be assigned to the `devel`

partition for 30 minutes, 1 core and 1GB memory.
Check and edit the VALET command in the `Makefile`

to load the appropriate version of the MATLAB Compile Runtime (`mcr`

) package. In this example, we edited the `Makefile`

to load `mcr/r2019b:nojvm`

, so the resulting output from the `make`

command produces:

[traine@r00n56 MCR]$ make Adding package `mcr/2019b:nojvm` to your environment make[1]: Entering directory `/home/2179/documents/matlab_example/MCR' mcc -o maxEig -I ./common -R ""-nojvm,-nodesktop,-singleCompThread"" -v -m maxEig.m Compiler version: 7.1 (R2019b) Dependency analysis by REQUIREMENTS. Parsing file "/home/1201/documents/matlab_example/MCR/maxEig.m" (referenced from command line). Generating file "/home/1201/documents/matlab_example/MCR/readme.txt". Generating file "run_maxEig.sh". make[1]: Leaving directory `/home/1201/documents/matlab_example/MCR'

Take note of the package added, and the files that are generated. You can remove these files, as they are not needed.
Remember the VALET command used to load the appropriate version of the `mcr`

package for compiling will also need to be the same command (same version of `mcr`

) used to run your compiled code either interactively or batch.

### Test interactively

To test interactively on the same compute node.

[traine@r00n56 MCR]$ vpkg_require mcr/r2019b:nojvm Adding package `mcr/2019b:nojvm` to your environment [traine@r00n56 MCR]$ time ./maxEig 20.8 maxe = 510.8787 real 6m58.608s user 6m38.486s sys 0m6.114s

#### back to the head node

When done, type `exit`

to terminate the `salloc`

interactive session and return to the login (head) node.

[traine@r00n56 MCR]$ exit exit salloc: Relinquishing job allocation 7861739 [(it_css:traine)@login00 MCR]$

### Test batch

#### Copy array job example

On the head node, copy the MCR array example project and the `matlab-mcr.qs`

template job script file into your current directory using the following commands

[(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ cp -r /opt/shared/templates/dev-projects/Projects/MCR MCR_array [(it_css:traine)@login00 ~]$ cd MCR_array [(it_css:traine)@login00 MCR_array]$ cp /opt/shared/templates/slurm/applications/matlab-mcr.qs . [(it_css:traine)@login00 MCR_array]$ make Adding package `mcr/2019b` to your environment make[1]: Entering directory `/home/2179/documents/matlab_example/MCR_array' mcc -o maxEig -I ./common -R ""-nojvm,-nodesktop,-singleCompThread"" -v -m maxEig.m Compiler version: 7.1 (R2019b) Dependency analysis by REQUIREMENTS. Parsing file "/home/2179/documents/matlab_example/MCR_array/maxEig.m" (referenced from command line). Generating file "/home/2179/documents/matlab_example/MCR_array/readme.txt". Generating file "run_maxEig.sh". make[1]: Leaving directory `/home/2179/documents/matlab_example/MCR_array'

The following lines will need to be changed or added to the `matlab-mcr.qs`

file. Please read through all the comments, but we have provided the line number preceding the code where the alteration is needed for this example. Keep in mind for this example we are compiling with `-single-comp-thread`

so we would not need to alternate to request additions cores (`--ntasks`

).

... 36 #SBATCH --mem=3G ... 54 #SBATCH --job-name=matlab_mcr_arrray ... 65 #SBATCH --partition=_workgroup_ ... 92 #SBATCH --output arrayJob-%A-%3a.out ... 117 # Setting the job array options 118 #SBATCH --array=1-100:1 ... 157 # Load a specific Matlab MCR package into the runtime environment: 158 # 159 vpkg_require mcr/r2019b:nojvm 160 161 # 162 # Do standard MCR environment setup: 163 # 164 . /opt/shared/slurm/templates/libexec/matlab-mcr.sh 165 166 # 167 # Execute your MCR program(s) here; prefix with UD_EXEC to 168 # ensure the job can/will respond to preemption/termination 169 # signals by calling your UD_JOB_EXIT_FN. 170 # 171 # Duplicate all three commands for each MCR program you run 172 # in sequence below. 173 # 174 #UD_EXEC my_mcr_program arg1 arg2 175 #mcr_rc=$? 176 #if [ $mcr_rc -ne 0 ]; then exit $mcr_rc; fi 177 178 echo "Job Running on Host: $HOSTNAME" 179 180 start=$(date "+%s") 181 echo "Job Start: ${start}" 182 183 #Using the Slurm task ID as an argurment lambda to MaxEig 184 let lambda=$SLURM_ARRAY_TASK_ID 185 186 #Lines Added for MCR_array example 187 UD_EXEC ${HOME}/documents/matlab_example/MCR_array/maxEig $lambda 188 mcr_rc=$? 189 if [ $mcr_rc -ne 0 ]; then exit $mcr_rc; fi 190 191 finish=$(date "+%s") 192 echo "Job Finish: ${finish}" 193 194 runtime=$(($finish-$start)) 195 196 echo "Total Runtime: ${runtime}"

Example `sbatch`

submission

[(it_css:traine)@login00 MCR]$ sbatch matlab-mcr.qs Submitted batch job 9803575 [(it_css:traine)@login00 MCR]$ date Fri Oct 30 08:57:58 EDT 2020 [(it_css:traine)@login00 MCR]$ date Fri Oct 30 08:58:19 EDT 2020 [(it_css:traine)@traine MCR]$ ls -l MCR_array-9803575* | wc -l 100

There are 100 output files with the names `MCR_array-9803575-001.out`

to `MCR_array-9803575-100.out`

For example, file 50 which is `MCR_array-9803575-050.out`

looks like this:

Adding package `mcr/2019b` to your environment -- Matlab MCR environment setup complete (on r00n13): -- MCR_ROOT = /opt/shared/matlab/r2019b -- MCR_CACHE_ROOT = /tmp/job_9803625 Job Running on Host: r00n13.localdomain.hpc.udel.edu Job Start: 1604062673 maxe = 525.9320 Job Finish: 1604062704 Total Runtime: 31

more examples *Under construction: Stay tuned*

## Compiling your code to use MATLAB engine

Here is an simple example function called

coded in Fortran, you can copy and use as a starting point.
**fengdemo.F**

On the head node and in your workgroup shell:

[(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ mkdir matlab_compile [(it_css:traine)@login00 matlab_example]$ cd matlab_compile [(it_css:traine)@login00 matlab_compile]$ vpkg_require matlab/r2019a gcc/9.1 [(it_css:traine)@login00 matlab_compile]$ cp $MATLABROOT/extern/examples/eng_mat/fengdemo.F . [(it_css:traine)@login00 matlab_compile]$ export LD_LIBRARY_PATH=$MATLABROOT/bin/glnxa64:$MATLABROOT/sys/os/glnx64:$LD_LIBRARY_PATH [(it_css:traine)@login00 matlab_compile]$ mex -client engine fengdemo.F Warning: MATLAB FORTRAN MEX Files are now defaulting to -largeArrayDims and 8 byte integers. If you are building a FORTRAN S-Function, please recompile using the -compatibleArrayDims flag. You can find more about adapting code to use 64-bit array dimensions at: https://www.mathworks.com/help/matlab/matlab_external/upgrading-mex-files-to-use-64-bit-api.html. Building with 'gfortran'. MEX completed successfully. [(it_css:triane)@login00 matlab_compile]

To run this program it will require running an interactive session on a compute node with X11 forwarding enabled. Here is an example for user `traine`

in workgroup `it_css`

:

[(it_css:traine)@login00 matlab_compile]$ salloc --x11 -N1 -n1 --partition=_workgroup_ salloc: Granted job allocation 7915683 salloc: Waiting for resource configuration salloc: Nodes r03g07 are ready for job [traine@r03g07 matlab_compile]$ vpkg_require matlab/r2019a gcc/9.1 Adding package `matlab/r2019a` to your environment Adding package `gcc/9.1.0` to your environment [traine@r03g07 matlab_compile]$ export LD_LIBRARY_PATH=$MATLABROOT/bin/glnxa64:$MATLABROOT/sys/os/glnx64:$LD_LIBRARY_PATH [traine@r03g07 matlab_compile]$ ./fengdemo

Shortly after starting to run the the program, `./fengdemo`

, a Matlab window will open and display a chart below

After the Matlab window is opened, you will see a prompt in the terminal to “Exit” or “Continue”. Typing `1`

and pressing the `Enter`

key will return a table which is shown below.

After the table is returned, close the MATLAB window with the Chart. Then use the `exit`

command to release the computer node.

Type 0 <return> to Exit Type 1 <return> to continue 1 MATLAB computed the following distances: time(s) distance(m) 1.00 -4.90 2.00 -19.6 3.00 -44.1 4.00 -78.4 5.00 -123. 6.00 -176. 7.00 -240. 8.00 -314. 9.00 -397. 10.0 -490. [traine@r03g07 matlab_compile]$ exit salloc: Relinquishing job allocation 7915683 [(it_css:traine)@login00 matlab_compile]$

## Compiling your own MATLAB function

There is an simple example function

, coded in c, you can copy and use as a starting point.
**timestwo.c**

On the head node and in a workgroup shell:

[(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ mkdir matlab_function [(it_css:traine)@login00 matlab_example]$ cd matlab_function [(it_css:traine)@login00 matlab_function]$ vpkg_require matlab/r2019a gcc/9.1 Adding package `matlab/r2019a` to your environment Adding package `gcc/9.1.0` to your environment [(it_css:traine)@login00 matlab_function]$ cp $MATLABROOT/extern/examples/refbook/timestwo.c . [(it_css:traine)@login00 matlab_function]$ mex timestwo.c Building with 'gcc'. Warning: You are using gcc version '9.1.0'. The version of gcc is not supported. The version currently supported with MEX is '6.3.x'. For a list of currently supported compilers see: https://www.mathworks.com/support/compilers/current_release. MEX completed successfully. [(it_css:traine)@login00 matlab_function]$

To start MATLAB on a compute node to test this new function:

[(it_css:traine)@login00 matlab_function]$ salloc --partition=devel salloc: Pending job allocation 7916296 salloc: job 7916296 queued and waiting for resources salloc: job 7916296 has been allocated resources salloc: Granted job allocation 7916296 salloc: Waiting for resource configuration salloc: Nodes r00n56 are ready for job [traine@r00n56 matlab_function]$ vpkg_require matlab/r2019a gcc/9.1 [traine@r00n56 matlab_function]$ matlab -nodesktop MATLAB is selecting SOFTWARE OPENGL rendering. < M A T L A B (R) > Copyright 1984-2019 The MathWorks, Inc. R2019a (9.6.0.1072779) 64-bit (glnxa64) March 8, 2019 To get started, type doc. For product information, visit www.mathworks.com. >>

Now test the function by typing `timestwo(4)`

. The results are shown below. Afterwards type `quit`

to exit Matlab and then type `exit`

to release the compute node.

>> timestwo(4) ans = 8 >> quit [traine@r00n56 matlab_function]$ exit exit salloc: Relinquishing job allocation 7916296 [(it_css:traine)@login00 matlab_function]$

# Batch job serial example

Second, write a shell script file to set the MATLAB environment and start MATLAB running your script file. The following script file will set the MATLAB environment and run the command in the script.m file:

[(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ mkdir matlab_slurm [(it_css:traine)@login00 matlab_example]$ cd matlab_slurm [(it_css:traine)@login00 matlab_slurm]$ cp /opt/shared/templates/slurm/generic/serial.qs batch.qs [(it_css:traine)@login00 matlab_slurm]$ vim batch.qs

- batch.qs
... 40 #SBATCH --job-name=script.m ... 50 #SBATCH --partition=_workgroup_ ... 67 #SBATCH --time=0-03:00:00 ... 76 #SBATCH --output %x-%j.out 77 #SBATCH --error %x-%j.out ... 86 #SBATCH --mail-user='traine@udel.edu' 87 #SBATCH --mail-type=END,FAIL,TIME_LIMIT_90 ... 137 # 138 # [EDIT] Add your script statements hereafter, or execute a script or program 139 # using the srun command. 140 # 141 #srun date 142 #Loading MATLAB 143 vpkg_require matlab/r2018b 144 #Running the matlab script 145 matlab -nodisplay -nojvm -batch script

Make sure you change the `--mail-user`

from `traine@udel.edu`

to your preferred email address. The `-nodisplay`

indicates no X11 graphics, which implies `-nosplash -nodesktop`

. The `-nojvm`

indicates no Java. (Java is needed for some functions, e.g., print graphics, but should be excluded for most computational jobs.)
The `-batch`

is followed by a Matlab command, enclosed in quotes when there is are spaces in the command.

**Errors in the Matlab script**: The command

`script`

will execute the lines in the `script.m`

file. For some errors Matlab will display the error message and wait for a response – clearly not appropriate for a batch job. Consider replacing `script`

with
the compound command
"try; script; catch ERR; disp(getReport(ERR,'extended')); quit; end"

The purpose of the ** try/catch** block is to catch the first error in the script, and display a report. With the

**option the report will include a stack trace at the point of the error.**

`extended`

**Graphics in the Matlab script**

- Do not include the
`-nojvm`

on the**matlab**command. - Do set paper dimensions and print each figure to a file.

The text output will be included in the standard Grid Engine output file, but not any graphics. All figures must be exported using the **print** command. Normally the **print** command will print on an 8 1/2 by 11 inch page with margins that are for a printed page of paper. The size and margins will not work if you plan to include the figure in a paper or a web page.

We suggest setting the current figure's `PaperUnits`

, `PaperSize`

and `PaperPosition`

. Matlab provides a handle to the current figure (**gcf**). For example, the commands

set(gcf,'PaperUnits','inches','PaperSize',[4,3],'PaperPosition',[0 0 4 3]); print('-dpng','-r100','maxe.png');

will set the current figure to be 4 x 3 inches with no margins, and then print the figure as a 400×300 resolution `png`

file.

### Submit job

Third, from the directory with `script.m`

, `maxEig.m`

and `batch.qs`

, submit the batch job with the command:

sbatch batch.qs

### Wait for completion

Finally, wait for the mail notification, which will be sent to `traine@udel.edu`

unless you changed it to your preferred email address. When the job is done, the output from the MATLAB command will be in a file with the pattern `script.m-«JOBID».out`

, where `JOBID`

is the number assigned to your job.

After waiting for about 2 or 3 hours, a message was received from SLURM Administrator. The email will have a title like the one shown below and there will be no content in the body.

SLURM Job_id=7937771 Name=script.m Ended, Run time 02:47:11, COMPLETED, ExitCode 0

### Gather results

The results for Job 7937771 are in the file

- script.m-7937771.out
Fri Apr 10 16:36:38 EDT 2020 Adding package `matlab/r2018b` to your environment < M A T L A B (R) > Copyright 1984-2018 The MathWorks, Inc. R2018b (9.5.0.944444) 64-bit (glnxa64) August 28, 2018 For online documentation, see https://www.mathworks.com/support For product information, visit www.mathworks.com. maxe = 70.0220 maxe = 71.7546 maxe = 70.8331 maxe = 70.5714 maxe = 69.4923 maxe = 67.7814 maxe = 70.5037 maxe = 68.3293 maxe = 69.5694 ... //Skipping 953 similar displays of variable maxe// maxe = 67.4221 Elapsed time is 10023.165546 seconds. avgMaxEig = 69.5131

### Timings and core count

Consider a batch job run with these Slurm options:

#SBATCH --ntasks=5 #SBATCH --mem=1G #SBATCH --job-name=script_opt.m

The `sbatch`

command will assign a `JOBID`

, and once it starts running, the `squeue`

command will show the node you are running on and we can use it to set `n=r01n17`

and refer to it as `$n`

for our series of next commands. After about 10 minutes of running:

[(it_css:traine)@login00 matlab_slurm]$ n=r01n17 [(it_css:traine)@login00 matlab_slurm]$ echo $n r01n17 [(it_css:traine)@login00 matlab_slurm]$ ssh $n ps -eo pid,ruser,pcpu,pmem,thcount,stime,time,command | egrep '(COMMAND|matlab)' PID RUSER %CPU %MEM THCNT STIME TIME COMMAND 10853 traine 100 0.6 12 13:56 00:19:53 /opt/shared/matlab/r2018b/bin/glnxa64/MATLAB -nodisplay -batch script -nojvm

This `ps`

command will give the percent CPU, which is `= >100%`

for multi-core jobs, the percent memory, the thread count, which is `> 5`

, the start time, the time of executions, and finally the full command used to the start the job.

Given the reported PID `10853`

, you can drill down and see which of the 10 threads are consuming CPU time:

[(it_css:traine)@login00 matlab_slurm]$ ssh $n ps -eLf | egrep '(PID|10853)' | grep -v ' 0 ' UID PID PPID LWP C NLWP STIME TTY TIME CMD traine 10853 10778 10906 99 12 13:56 ? 00:27:05 /opt/shared/matlab/r2018b/bin/glnxa64/MATLAB -nodisplay -batch script -nojvm

While the batch job was running on node `r01n17`

, the `top`

command was run to sample the resources being used by MATLAB
every second `-b -n 1`

and can only be used on computing nodes you have jobs running. The `-H`

option was used to display each individual thread, rather than a summary of all threads in a process.

[(it_css:traine)@login00 matlab_slurm]$ ssh $n top -H -b -n 1 | egrep '(COMMAND|MATLAB)' | grep -v 'S 0' PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 10906 traine 20 0 2450792 859664 105120 R 99.9 0.7 28:47.25 MATLAB

[(it_css:traine)@login00 matlab_slurm]$ qhost -h $n HOSTNAME ARCH NCPU NSOC NCOR NTHR NLOAD MEMTOT MEMUSE SWAPTO SWAPUS ---------------------------------------------------------------------------------------------- r01n17 E5-2695v4 36 2 36 36 0.03 124.0G 1024.0M 0.0 0.0

After the job is done you can use `sacct`

to get a recap of resources used:

[(it_css:traine)@login00 matlab_slurm]$ sacct -N r01n17 -j 7935464 -o jobName,jobID,Nodelist,maxVMSize,MaxRSS,CPUTime,Start,End,Elapsed,State JobName JobID NodeList MaxVMSize MaxRSS CPUTime Start End Elapsed State ---------- ------------ --------------- ---------- ---------- ---------- ------------------- ------------------- ---------- ---------- script_op+ 7935464 r01n17 14:06:35 2020-04-10T13:56:18 2020-04-10T16:45:37 02:49:19 COMPLETED batch 7935464.bat+ r01n17 209328K 755008K 14:06:35 2020-04-10T13:56:18 2020-04-10T16:45:37 02:49:19 COMPLETED extern 7935464.ext+ r01n17 182456K 20K 14:06:40 2020-04-10T13:56:18 2020-04-10T16:45:38 02:49:20 COMPLETED date 7935464.0 r01n17 277996K 488K 00:00:05 2020-04-10T13:56:21 2020-04-10T13:56:22 00:00:01 COMPLETED

# Batch job parallel example

The MATLAB Parallel Computing toolbox uses JVM to manage the workers and communicate while you are running. You
need to setup the MATLAB pools in your `script`

.

### Matlab parallel script

Here is the slightly modified MATLAB script.

Add the necessary commands to configure your `parcluster`

and `parpool`

, and change `for`

⇒ `parfor`

.

- pscript.m
% script to run maxEig function 200 times %% Configure parpool myCluster = parcluster('local'); myCluster.NumWorkers = str2double(getenv('SLURM_NTASKS')); myCluster.JobStorageLocation = getenv('TMPDIR'); myPool = parpool(myCluster, myCluster.NumWorkers); count = 200; dim = 5001; sumMaxe = 0; tic parfor i=1:count; sumMaxe = sumMaxe + maxEig(i,dim); end toc avgMaxEig = sumMaxe/count delete(myPool); exit

### Slurm parallel script

Remove the option `-nojvm`

, because JVM is needed for the Parallel Computing toolbox commands.
Copy the template `matlab.qs`

script and name it `pbatch.qs`

by typing

cp /opt/shared/templates/slurm/applications/matlab.qs ./pbatch.qs

Make the following changes to the code

- pbatch.qs
... 19 #SBATCH --ntasks=20 ... 37 #SBATCH --mem=60G ... 54 #SBATCH --job-name=matlab-pscript ... 65 #SBATCH --partition=_workgroup_ ... 75 #SBATCH --time=0-01:00:00 ... 82 #SBATCH --time-min=0-00:30:00 ... 90 #SBATCH --output=%x-%j.out 91 #SBATCH --error=%x-%j.out ... 155 vpkg_require matlab/r2019b ... 170 UD_EXEC matlab -nodisplay -batch pscript

### Timing results

Reported usage for same job run using the parallel toolbox.

[(it_css:traine)@login00 matlab_slurm]$ sacct -j 7994763,7997035 -o jobName,jobID,Nodelist,maxVMSize,MaxRSS,CPUTime,Start,End,Elapsed,State JobName JobID NodeList MaxVMSize MaxRSS CPUTime Start End Elapsed State ---------- ------------ --------------- ---------- ---------- ---------- ------------------- ------------------- ---------- ---------- script.m 7994763 r01n49 4-05:01:12 2020-04-15T11:16:06 2020-04-15T14:04:28 02:48:22 COMPLETED batch 7994763.bat+ r01n49 209328K 804888K 4-05:01:12 2020-04-15T11:16:06 2020-04-15T14:04:28 02:48:22 COMPLETED extern 7994763.ext+ r01n49 107904K 20K 4-05:01:12 2020-04-15T11:16:06 2020-04-15T14:04:28 02:48:22 COMPLETED pscript 7997035 r03n38 09:33:20 2020-04-15T15:56:42 2020-04-15T16:11:02 00:14:20 COMPLETED batch 7997035.bat+ r03n38 209460K 14462792K 09:33:20 2020-04-15T15:56:42 2020-04-15T16:11:02 00:14:20 COMPLETED extern 7997035.ext+ r03n38 107952K 0 09:33:20 2020-04-15T15:56:42 2020-04-15T16:11:02 00:14:20 COMPLETED

Compare script vs pscript

Job | Elapsed Time | CPUTime | Max RSS |
---|---|---|---|

script.m | 02:48:22 | 4-05:01:12 | 804888K |

pscript | 00:19:35 | 09:33:20 | 14462792K |

The job **script** used more CPU resources with the multiple computational threads, while **pscript** user more memory resources with 20 single-threaded worker.

# Interactive job example

The basic steps to running a MATLAB interactively on a compute node that will dedicate specific resources to your job.

### Scheduling interactive job

Create a directory and add maxEig.m and script.m to it.

[(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ mkdir matlab_interact [(it_css:traine)@login00 matlab_example]$ cp maxEig.m script.m matlab_interact/ [(it_css:traine)@login00 matlab_example]$ cd matlab_interact [(it_css:traine)@login00 matlab_interact]$ ls maxEig.m script.m

Start an interactive session on a compute node with the `salloc`

command. You will also want to include the options for the number of cores `ntasks`

and `–partition=_workgroup_`

.

[(it_css:traine)@login00 matlab_interact]$ salloc --partition=_workgroup_ --ntasks=20 salloc: Pending job allocation 7985695 salloc: job 7985695 queued and waiting for resources salloc: job 7985695 has been allocated resources salloc: Granted job allocation 7985695 salloc: Waiting for resource configuration salloc: Nodes r01n10 are ready for job [traine@r01n10 matlab_interact]$

### Starting a command mode matlab session

[traine@r01n10 matlab_interact]$ vpkg_require matlab/r2019b Adding package `matlab/r2019b` to your environment [traine@r01n10 matlab_interact]$

[traine@r01n10 matlab_interact]$ matlab -nodesktop -nosplash MATLAB is selecting SOFTWARE OPENGL rendering. < M A T L A B (R) > Copyright 1984-2019 The MathWorks, Inc. R2019b (9.7.0.1190202) 64-bit (glnxa64) August 21, 2019 To get started, type doc. For product information, visit www.mathworks.com. >>

### Using help as the first command

>> help maxEig maxEig Maximum Eigenvalue of a random matrix Input parameters sd - seed for uniform random generator dim - size of the square matrix (should be odd) Output value maxe - maximum real eigvalue

### Calling function once

Use the tic and toc commands to report the elapsed time to generate the random matrix, find all eigenvalues and report the maximum real eigenvalue.

>> tic; maxEig(1,5001); toc maxe = 70.0220 Elapsed time is 54.781289 seconds.

### Finishing up

>> exit [traine@r01n10 matlab_interact]$ exit exit salloc: Relinquishing job allocation 7985695 [(it_css:traine)@login00 matlab_interact]$

## Interactive parallel toolbox example

This example is based on the `matlab_interact`

directory that was created in the Interactive job example demo shown above.

When you using the parallel toolbox, you should logon to a compute node using a workgroup partition and the number of tasks and memory required:

[(it_css:traine)@login00 matlab_interact]$ salloc --partition=_workgroup_ --ntasks=20 --mem=40G salloc: Pending job allocation 7993736 salloc: job 7993736 queued and waiting for resources salloc: job 7993736 has been allocated resources salloc: Granted job allocation 7985815 salloc: Waiting for resource configuration salloc: Nodes r00g01 are ready for job [traine@r00g01 matlab_interact]$ vpkg_require matlab/r2019b [traine@r00g01 matlab_interact]$ matlab -nodesktop -nosplash

This will effectively reserve 20 cpus and 40G of memory for your interactive job. The default number of parallel workers when using the parallel toolbox is 12 but you can define the number workers based on the number of tasks requested.

Here we request 20 workers with the `parpool`

function, and then use `parfor`

to send a different seed to each worker. The output is from the workers, as they complete, but the order is not deterministic.

**Make sure the workers are not doing exactly the same computations**In this example, the different seed, passed to the function, causes all the random values to be different on each worker.

It took about 100 seconds for all 20 workers to produce a result, however since there are 20 workers working in parallel the elapsed time to complete 200 results is about 918 seconds.

MATLAB is selecting SOFTWARE OPENGL rendering. < M A T L A B (R) > Copyright 1984-2019 The MathWorks, Inc. R2019b (9.7.0.1190202) 64-bit (glnxa64) August 21, 2019 To get started, type doc. For product information, visit www.mathworks.com. >> myCluster = parcluster('local'); >> myCluster.NumWorkers = str2double(getenv('SLURM_NTASKS')); >> myCluster.JobStorageLocation = getenv('TMPDIR'); >> myPool = parpool(myCluster, myCluster.NumWorkers); Starting parallel pool (parpool) using the 'local' profile ... Connected to the parallel pool (number of workers: 20). >> tic; parfor sd = 1:200; maxEig(sd,5001); end; toc maxe = 67.1320 maxe = 70.8721 maxe = 71.3507 ... skipped lines ... maxe = 70.7506 maxe = 70.2656 maxe = 71.4253 Elapsed time is 918.822702 seconds.

Once the job is completed, delete your pool and exit MATLAB, and release the interactive compute node by typing `exit`

.

>> delete(myPool); Parallel pool using the 'local' profile is shutting down. >> exit [traine@r00g01 matlab_interact]$ exit exit salloc: Relinquishing job allocation 7993736 [(it_css:traine)@login00 matlab_interact]$

# MCR array job example

Most Matlab functions can be compiled using the Matlab Compiler (`mcc`

) and then deployed to run on the compute nodes in the MATLAB Compiler Runtime (MCR). The MCR is a prerequisite for deployment, and is installed on all the compute nodes. You must use VALET to set up the libraries you will need to run your function from the command line. You should **NOT** to use the shell (`.sh`

file) that the Matlab compiler creates.

There are two ways to run compiled MATLAB jobs in a shared environment, such as Caviness.

- Compile to produce an executable that uses a single computational thread specifying the MATLAB option
`-singleCompThread`

- Submit the job to use the nodes exclusively specifying the Slurm option
`–exclusive`

You can run more jobs on each node when they are compiled using just one core (Single Computational Thread). This will give you higher throughput for an array job, but not higher performance.

### Example compiler commands

Make a new directory `MCR_array_II`

directory and then copy maxEig function from the matlab_example directory to the new `MCR_array_II`

directory.

[(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ mkdir MCR_array_II [(it_css:traine)@login00 matlab_example]$ cp maxEig.m MCR_array_II/ [(it_css:traine)@login00 matlab_example]$ cd MCR_array_II

The maxEig function has a conditional statement to make it work when deployed.

if (isdeployed) sd = str2num(sd) dim = str2num(dim) end

All arguments of the function are taken as tokens on the shell command used to execute the script, and they are all strings. You must convert numbers from strings to numbers. You can use the same variable names so that the rest of the script will behave the same when deployed or executed directly in Matlab.

You can convert this function into a single computational executable by using the Matlab compiler `mcc`

. To do this, create a file `compile.sh`

and add the below line to the file.

prog=maxEig opt='-nojvm,-nodisplay,-singleCompThread' version='r2019a' vpkg_require matlab/$version mcc -R "$opt" -mv $prog.m [ -d ${WORKDIR}/${USER}/sw/bin ] && mv $prog ${WORKDIR}/${USER}/sw/bin

**Keep these commands in a file**: Even though this is just two commands, we recommend you keep these commands, including the shell assignment statements, as a record of the MATLAB version and options you used to create the executable

`maxEig`

. You will need to know these if you want to use the executable in a shell script. You can source this file when you want to rebuild `maxEig`

**You can get mcc usage instructions with**: The string following the

`mcc -help`

`-R`

flag are the Matlab
options you want to use at run time. The `-m`

option tell mcc to build a standalone application to be deployed
using MCR. The `-v`

option is for verbose mode.
`lustre`

file system. That is why the executable **is moved to the special directory, which is added to your path when a new workgroup shell is started or when a queue script is submitted.**

`$prog`

[ -d $WORKDIR/sw/bin ] && mv $prog $WORKDIR/sw/bin

### Compiling commands

Make the directory where the MaxEig function will be placed when the function is compiled.

[(it_css:traine)@login00 MCR_array_II]$ mkdir -p ${WORKDIR}/${USER}/sw/bin

Now request a interactive compute node and run the `compile.sh`

script.

[(it_css:traine)@login00 MCR_array_II]$ salloc --partition=devel salloc: Granted job allocation 9804138 salloc: Waiting for resource configuration salloc: Nodes r00n56 are ready for job [traine@r00n56 MCR_array_II]$ ls compile.sh maxEig.m [traine@r00n56 MCR_array_II]$ . compile.sh Adding package `matlab/r2019b` to your environment Compiler version: 7.1 (R2019b) Dependency analysis by REQUIREMENTS. Parsing file "/home/1201/matlab_example/MCR_array_II/maxEig.m" (referenced from command line). Generating file "/home/1201/matlab_example/MCR_array_II/readme.txt". Generating file "run_maxEig.sh". [traine@r00n56 MCR_array_II]$ ls compile.sh maxEig.m mccExcludedFiles.log readme.txt requiredMCRProducts.txt run_maxEig.sh [traine@r00n56 MCR_array_II]$ exit exit salloc: Relinquishing job allocation 9804138 [(it_css:traine)@login01 MCR_array_II]$

### Example queue script file

The `mcc`

command will generate a `.sh`

file should **not** be used. This run script does not use VALET and does not have the appropriate Slurm commands. Instead, you should copy the Slurm template in the file
`/opt/shared/templates/slurm/applications/matlab-mcr.qs`

by using the following command

[(it_css:traine)@login00 MCR_array_II]$ cp /opt/shared/templates/slurm/applications/matlab-mcr.qs .

and make the appropriate changes below changes.

... 20 #SBATCH --ntasks=2 ... 29 #SBATCH --mem=3G ... 47 #SBATCH --job-name=maxEig ... 58 #SBATCH --partition=_workgroup_ ... 85 #SBATCH --output %x-%A-%3a.out ... 102 # Setting the job array options 103 #SBATCH --array=1-200:1 ... 148 # Load a specific Matlab MCR package into the runtime environment: 149 # 150 vpkg_require mcr/r2019b:nojvm 151 export MCR_CACHE_ROOT="$TMPDIR" 152 153 # 154 # Do standard MCR environment setup: 155 # 156 . /opt/shared/slurm/templates/libexec/matlab-mcr.sh 157 158 # 159 date "+Start %s" 160 echo "Host ${HOSTNAME}" 161 162 163 #Getting the ask ID that will be passed as a argument 164 let seed=$SLURM_ARRAY_TASK_ID 165 let dim=5001 166 167 # Execute your MCR program(s) here; prefix with UD_EXEC to 168 # ensure the job can/will respond to preemption/termination 169 # signals by calling your UD_JOB_EXIT_FN. 170 # 171 # Duplicate all three commands for each MCR program you run 172 # in sequence below. 173 # 174 #UD_EXEC my_mcr_program arg1 arg2 175 #mcr_rc=$? 176 #if [ $mcr_rc -ne 0 ]; then exit $mcr_rc; fi 177 UD_EXEC ${WORKDIR}/${USER}/sw/bin/maxEig $seed $dim 178 mcr_rc=$? 179 if [ $mcr_rc -ne 0 ]; then exit $mcr_rc; fi 180 181 date "+Finish %s" 182

The two `date`

commands record the start and finish time in seconds for each task. These are then used to compute the total runtime. The echoed host name can be used to calculate the overlapping use of the computer nodes. Since `maxEig`

was compiled as a single threaded job the elapse time will be very close to the wall clock time and CPU time. We do not send email notification since it would generated 200 email messages, one for each task.

### Running Compiled Matlab Example In Workgroup And Analyzing Output Results

To test the example compiled Matlab job on the `it_css`

owner queues, we first compiled the code with mcc and
then submited with sbatch.

[(it_css:traine)@login00 MCR_array_II]$ sbatch matlab-mcr.qs Submitted batch job 9805558

The assigned job number ID assigned is 9805282. After a few minutes 200 files were created in the current directory.

maxEig-9805558-001.out ... maxEig-9805558-200.out

They each had the output of one task. For example for taskid 125:

Adding package `mcr/2019b:nojvm` to your environment -- OpenMP job setup complete: -- OMP_THREAD_LIMIT = 2 -- OMP_PROC_BIND = true -- OMP_PLACES = cores -- MP_BLIST = 32,33 -- Matlab MCR environment setup complete (on r00n10): -- MCR_ROOT = /opt/shared/matlab/r2019b -- MCR_CACHE_ROOT = /tmp/job_9805684 Start 1604084921 Host r00n10.localdomain.hpc.udel.edu sd = 125 dim = 5001 maxe = 70.4891 Finish 1604085004

Now we will use wikigather.pl to gather all the information from this files and return the avgMaxEig value.
User the link to copy the code perl code, and them create new file in your current directory with that same name `wikigather.pl`

and add the copied code into that file.

**your job id**

[(it_css:traine)@login00 MCR_array_II]$ perl wikigather.pl avgMaxEig = 69.5131125

The script will all create three new .data files and one new .txt file. We are really on interested in the results8012246.data and the wikimaxEig.txt files. Examples of them are shown below.

sd dim maxe 1 5001 70.0220 2 5001 71.7546 3 5001 70.8331 4 5001 70.5714 5 5001 69.4923 .... 195 5001 68.7440 196 5001 71.5652 197 5001 69.8530 198 5001 70.1213 199 5001 70.7535 200 5001 67.4221

These are the same results we got from both the matlab loop and the parallel toolbox, but they where computed in just about 8.5 minutes. To see this we gather the start/finish times in seconds and the host name.

#### wiki9805558.txt Output:

SGE array job started Fri 30 Oct 2020 03:04:16 PM EDT

Used a total of 16585 CPU seconds over 525 seconds of elapsed time on 2 nodes

Node | Real Clock Time | Ratio | |||
---|---|---|---|---|---|

Name | Count | Min | Max | Average | User/Real |

r00n10.localdomain.hpc.udel.edu | 108 | 82.00 | 85.00 | 83.32 | 1.00000 |

r00n47.localdomain.hpc.udel.edu | 92 | 58.00 | 84.00 | 82.46 | 1.00000 |

Using gnuplot we get a time chart of usage on the 2 nodes and total CPU usage.
Create a file and add the following code to a file named `plot«JOB ID».gnuplot`

.

set terminal png size 640,640 set output "wiki9805558.png" set multiplot layout 2,1 set xrange [0:550] set yrange [0:80] set key on set title "Tasks on 2 nodes by time (seconds)" set key on plot "count.data" u 1:3 t "r00n10.localdomain.hpc.udel.edu" w filledcurves,"count.data" u 1:2 t "r00n47.localdomain.hpc.udel.edu" w filledcurves set title "User time usage rate on all nodes" plot "usage.data" u 1:2 w steps t "CPU"

To create the plot we will need to request an interactive compute node on the devel partition. Once the request has been filled we will need to use VALET to load the gnuplot application and run the `plot«JOB ID».gnuplot`

script that we just created. After the script is ran we will release the node and then view the `.png`

that was created by the script.

[(it_css:traine)@login00 MCR_array_II]$ salloc --partition=devel salloc: Granted job allocation 9805971 salloc: Waiting for resource configuration salloc: Nodes r00n56 are ready for job [traine@r00n56 MCR_array_II]$ vpkg_require gnuplot Adding package `gnuplot/5.2.4` to your environment [traine@r00n56 MCR_array_II]$ gnuplot plot9805558.gnuplot [traine@r00n56 MCR_array_II]$exit [(it_css:traine)@login00 MCR_array_II]$ display wiki9805558.png

An example of the `.png`

file that is created by the plot9805558.gnuplot script.

### Perl Script For Compiled Matlab

**DO NOT COPY AND PASTE THIS CODE IT MOSTLY LIKELY NOT FORMAT CORRECTLY AND BREAK THE CODE. INSTEAD DOWNLOAD THE FILE WITH**

`WGET`

DIRECTLY TO THE LOCATION YOU WOULD LIKE IT. YOU COULD ALSO DOWNLOAD IT LOCALLY AND WITH SCP TRANSFER TO BACK TO CAVINESS.- wikigather.pl
$pattern = '\-(9805558)\-(\d+)\.(out)'; # Make sure to change 9805558 to make your job id. $countFile = 'count.data'; # task count on nodes by seconds $usageFile = 'usage.data'; # accumulate user time on all nodes by seconds $nodeUsageFile = "nodeusage.data"; #detail of node usage by seconds $nodeUsageFiles = "%s_usage.data"; # %s -> host @varNames = qw/sd dim maxe/; # used for columns in resultfile $resultFile = "result%s.data"; # %s -> project id &scandir("."); @node = sort keys %hostCount; foreach $jobid (keys %startTime) { my $file = sprintf "wiki%s.txt", $jobid; open(WIKI, ">$file"); print WIKI `date -d \@$startTime{$jobid} +\"SGE array job started %c\n"`; print WIKI "Used a total of $userTotal{$jobid} CPU seconds "; print WIKI "over ",$stopTime{$jobid}-$startTime{$jobid}," seconds of elapsed time "; print WIKI "on ",0+@node," nodes\n"; $baseTime = $startTime{$jobid} if (!defined $baseTime or $startTime{$jobid} < $baseTime); $avgMaxEig=0; $count=0; if ($resultFile) { my $file = sprintf $resultFile, $jobid; open(DATA, ">$file"); print DATA "@varNames\n"; foreach $task (sort { $a <=> $b } keys %{$result{$jobid}}) { my %var = split($;,$result{$jobid}{$task}); print DATA "@var{@varNames}\n"; $avgMaxEig += $var{'maxe'}; $count += 1; } close(DATA); print 'avgMaxEig = ', $avgMaxEig/$count, "\n"; } printf WIKI "^ %18s ^^ %30s ^^^ %12s ^\n","Node ","Real Clock Time ","Ratio "; printf WIKI "^ %8s ^ %8s ^ %9s ^ %9s ^ %9s ^ %12s ^\n","Name ","Count ","Min ","Max ","Average ","User/Real "; foreach (@node) { if ( $hostCountByJob{$jobid}{$_} > 0) { printf WIKI "|%8s|%8d| %9.2f|%9.2f|%9.2f |%12.5f|\n", $_, $hostCountByJob{$jobid}{$_}, $hostRealMin{$jobid}{$_},$hostRealMax{$jobid}{$_}, $hostReal{$jobid}{$_}/$hostCountByJob{$jobid}{$_}, $hostUser{$jobid}{$_}/$hostReal{$jobid}{$_}; } } close(WIKI); } if ($countFile and open(DATA,">$countFile")) { my(@col,%byNode,$time,$count); $col[$_] = 0 for $[ .. $#node; foreach $time (sort { $a <=> $b } keys %timeCount) { printf DATA "%d %s\n", $time-$baseTime, "@col"; $byNode{$_} += $timeCount{$time}{$_} foreach keys %{$timeCount{$time}}; $count=0; $col[$_] = $count += $byNode{$node[$_]} for $[ .. $#node; printf DATA "%d %s\n", $time-$baseTime, "@col"; } close(DATA); } if ($usageFile and open(DATA,">$usageFile")) { my ($time, $lastTime, $slope, $usage); foreach $time (sort { $a <=> $b } keys %timeRate) { $usage += $slope*($time - $lastTime); $slope += $timeRate{$time}{$_} foreach keys %{$timeRate{$time}}; printf DATA "%d %.4f %.4f\n", $time-$baseTime, $slope, $usage; $lastTime = $time; } close(DATA); } if ($countFile and $usageFile) { foreach $jobid (keys %startTime) { my $plotTitle = 'Number of tasks on %s by time (seconds)'; # %s -> nodes my(@plot); $plot[$_] = "\"$countFile\" u 1:".(2+$_-$[)." t \"$node[$_]\" w filledcurves" for $[ .. $#node; my $plotTop = join(",",reverse @plot); my $titleTop = sprintf $plotTitle, 0+@node." nodes"; my $key = "off"; my ($t1,$t2) = (30*int(($startTime{$jobid}-$baseTime)/30),30*int(2+($stopTime{$jobid}-$baseTime)/30)); $titleTop = sprintf $plotTitle, "nodes @node" if $#node < 5; $key = "out horiz top right" if $#node < 9; open (PLOT, "| gnuplot" ); print PLOT <<"EOP"; set term pngcairo font "sans,10" size 640,640 set output "wiki$jobid.png" set multiplot layout 2,1 set xrange [$t1:$t2] set key $key set ylabel "Number of Tasks on node" plot $plotTop set key out horiz top right set ylabel "Total CPU usage" set xlabel "Time (seconds)" plot "$usageFile" u 1:3 w lines t "CPU seconds" EOP } } sub scanfile { my($file) = @_; my($jobid,$taskid) = ($file =~ /$pattern/); my($host,$start,$finish,$usr1,$usr2,$real,$user,$sys,$lhs,%var); open(FILE,$file) || next; local $/ = undef; #Read file as one string while (<FILE>) { study; /^Host (\S+)/m and $host=$1; /^Start (\d+)/m and $start=$1; /^Finish (\d+)/m and $finish=$1; /^SIGUSR1 (\d+)/m and $usr1=$1; /^SIGUSR2 (\d+)/m and $usr2=$1; /^real(.*?)m(.*?)s/m and $real=60*$1+$2; /^user(.*?)m(.*?)s/m and $user=60*$1+$2; /^sys(.*?)m(.*?)s/m and $sys=60*$1+$2; while(/(\S+)\s*=\s*(.*)/g) { $var{$1}=$2 }; } close(FILE); $result{$jobid}{$taskid} = join($;,%var); $SGEfile{$file} = sprintf "| %s | %.2f %8.2f %8.2f |", $host, $real, $user, $sys; $SGEfile{$file} .= sprintf " %d %d |", $usr1, $usr2; $SGEfile{$file} .= join(',', map {" $_=$var{$_}"} keys %var ); $finish = $usr2 if( $finish==0 ); $finish = $usr1 if( $finish==0 ); $finish > 0 || next; $real = $finish-$start if($real==0); $user = $real-$sys if($user==0); $startTime{$jobid} = $start if (!defined $startTime{$jobid} or $start < $startTime{$jobid}); $stopTime{$jobid} = $finish if (!defined $stopTime{$jobid} or $finish > $stopTime{$jobid}); $userTotal{$jobid} += $user; $hostCount{$host} += 1; $hostCountByJob{$jobid}{$host} += 1; $hostReal{$jobid}{$host} += $real; $hostRealMax{$jobid}{$host} = $real if (!defined $hostRealMax{$jobid}{$host} or $real > $hostRealMax{$jobid}{$host}); $hostRealMin{$jobid}{$host} = $real if (!defined $hostRealMin{$jobid}{$host} or $real < $hostRealMin{$jobid}{$host}); $hostUser{$jobid}{$host} += $user; $timeCount{$start}{$host} += 1; $timeCount{$finish}{$host} -= 1; $timeRate{$start}{$host} += $user/($finish-$start); $timeRate{$finish}{$host} -= $user/($finish-$start); } sub scandir { my($basedir) = @_; my(@file,@dir); opendir(DIR, $basedir) || return; foreach ( grep (/^[^\.]/,readdir(DIR)) ) { # ignore hidden files next if -l "$basedir/$_" ; # skip sym links push @file,$_ if /$pattern/; # save files with this pattern push @dir,$_ if -d "$basedir/$_" ; # save directories for recursion } closedir(DIR); foreach (@file) { &scanfile("$basedir/$_"); } foreach (@dir) { &scandir("$basedir/$_"); } }

# Adding checkpoints Matlab job example

Adding checkpoints to your Matlab job could help it to gracefully handle kill signals from the system. The proper handling of these signals can help you restart your job without having to start completely over again. In the following example, we will modify previously used scripts and functions to track which interval the loop stops at when the job times out.

### Gathering code for job example

First we'll create a new directory and copy the needed code into it.

[(it_css:traine)@login00 ~]$ cd matlab_example [(it_css:traine)@login00 matlab_example]$ mkdir matlab_checkpoint [(it_css:traine)@login00 ~]$ cd matlab_checkpoint [(it_css:traine)@login00 matl_checkpoint]$ cp /opt/shared/templates/slurm/generic/serial.qs batch.qs

You will also want to put a copy of the maxEig.m and script.m into your `matlab_checkpoint`

directory.

Now we will need to make changes to `script.m`

.

% script to run maxEig function 200 times and print average. count = 200; dim = 5001; sumMaxe = 0; i = 0; tic; for i=1:count; sumMaxe = sumMaxe + maxEig(i,dim); counter = "counter: "+i; %Add this line disp(counter); %Add this line end; toc avgMaxEig = sumMaxe/count quit

The following changes will need to be added to batch.qs

... 40 #SBATCH --job-name=checkpoint ... 60 #SBATCH --time=0-01:30:00 ... 75 #SBATCH --output %x-%j.out 76 #SBATCH --error %x-%j.out ... 85 #SBATCH --mail-user='traine@udel.edu' 86 #SBATCH --mail-type=END,FAIL,TIME_LIMIT_90 ... 108 job_exit_handler() { 109 counter=$(tail -n 2 ${SLURM_JOB_NAME}-${SLURM_JOB_ID}.out | head -n 1) 110 echo "Job ${SLURM_JOB_NAME} ended on ${counter}" 111 #matlab -nodisplay -nojvm -batch disp(getReport(err,'extended')); quit;" 112 # Copy all our output files back to the original job directory: 113 #cp * "$SLURM_SUBMIT_DIR" 114 115 # Don't call again on EXIT signal, please: 116 trap - EXIT 117 exit 0 118 } 119 export UD_JOB_EXIT_FN=job_exit_handler ... 142 # 143 #srun date 144 export UD_JOB_EXIT_FN_SIGNALS="SIGTERM EXIT" 145 #Loading MATLAB 146 vpkg_require matlab/r2018b 147 #Running the matlab script 148 UD_EXEC matlab -nodisplay -nojvm -batch "try; script; catch ERR; disp(job_exit_handler(ERR.getReport)); quit; end"

### Running the checkpoint job and its output

We know from the MCR example that this script takes between 2-3 hours to run. In the changes we made to `batch.qs`

script, we set the wall clock to 1 hour and 30 minutes. That should insure that this script will fail to complete before the wall clock runs out of time. This is shown in the following job submission example.

[(it_css:traine)@login01 matlab_checkpoint]$ sbatch batch.qs Submitted batch job 8382365

After the wall clock runs out we will see the following output.

[(it_css:traine)@login01 matlab_checkpoint]$ tail -n 30 checkpoint-8382365.out 65.5558 counter: 105 maxe = 70.1761 counter: 106 maxe = 68.9765 counter: 107 maxe = 69.9773 counter: 108 maxe = 69.3456 counter: 109 slurmstepd: error: *** JOB 8382365 ON r00n47 CANCELLED AT 2020-05-20T19:58:11 DUE TO TIME LIMIT *** Job checkpoint ended on counter: 109

Now we know that the script completed about 100 of the 200 loop intervals before the wall clock expired. This example could be expanded to allow the job to be re-queued (by using the Slurm option `–requeue`

) and start at the last loop interval instead of restarting from the beginning if the logic in the `script.m`

is modified accordingly.

[(it_css:triane)@login01 matlab_checkpoint]$ sbatch batch.qs Submitted batch job 8390581 [(it_css:traine)@login01 matlab_checkpoint]$ scancel 8390581 [(it_css:traine)@login01 matlab_checkpoint]$ cat checkpoint-8390581.out -- Registered exit function 'job_exit_handler' for signal(s) SIGTERM Adding package `matlab/r2018b` to your environment < M A T L A B (R) > Copyright 1984-2018 The MathWorks, Inc. R2018b (9.5.0.944444) 64-bit (glnxa64) August 28, 2018 For online documentation, see https://www.mathworks.com/support For product information, visit www.mathworks.com. maxe = 70.0220 counter: 1 ... maxe = 67.7814 counter: 6 maxe = 70.5037 counter: 7 slurmstepd: error: *** JOB 8390581 ON r00n17 CANCELLED AT 2020-05-21T10:55:03 *** Job checkpoint ended on counter: 7