Materials Studio: Difference between revisions

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The example below assumes that you have installed Materials Studio 2018 according to the instructions above.  
The example below assumes that you have installed Materials Studio 2018 according to the instructions above.  


{{File|content=
{{File|contents=


#!/bin/bash
#!/bin/bash

Revision as of 14:32, 8 May 2018

Compute Canada does not have permission to install Materials Studio centrally on all clusters. However, if you do have access to Materials Studio, you will find below a recipe to install it easily on our clusters.

Installing Materials Studio 2018[edit]

Note

This recipe has been tested for Materials Studio 2018.


If you have access to Materials Studio 2018, you will need two things to proceed. First, you will need to have the archive file that contains the installer. This file should be named MaterialsStudio2018.tgz. Second, you will need to have the IP address and the port of the license server that you are going to use to connect to.

Once you have these, upload the MaterialsStudio2018.tgz file to your home folder on the cluster you intend to use. Then, run the command

Question.png
[name@server ~]$ MS_LICENSE_SERVER=<port>@<server> eb MaterialsStudio-2018-dummy-dummy.eb --sourcepath=$HOME

Once this command has completed, log out from the cluster and log back in. You should then be able to load the module through:

Question.png
[name@server ~]$ module load materialsstudio/2018

In order to be able to access the license server from the compute nodes, you will need to contact our technical support so that we can open our firewall and give you the IP addresses from which the license server needs to accept requests from.

Example of job submission script[edit]

The example below assumes that you have installed Materials Studio 2018 according to the instructions above.


File : file.txt

#!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=32
#SBATCH --time=12:00:00

module load materialsstudio/2018

# Create a list of nodes to be used for the job
DSD_MachineList="machines.LINUX"
slurm_hl2hl.py --format HP-MPI > $DSD_MachineList
export DSD_MachineList

# Job to run
RunDMol3.sh -np $SLURM_NTASKS Brucite001f