Materials Studio: Difference between revisions

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Compute Canada does not have permission to install Materials Studio centrally on all clusters. However, if you do have valid Materials Studio licence(s) and software, below is a recipe will assist installing it in Compute Canada clusters in your account.

= Installing Materials Studio 2018 = {{Panel|title=Note|panelstyle=SideCallout|content=This recipe has been tested with Materials Studio 2018. }}

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

Once you have these, upload the <tt>MaterialsStudio2018.tgz</tt> file to your /home folder on the cluster you intend to use. Then, run the command {{Command|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:

{{Command|module load materialsstudio/2018}}

In order to be able to access the license server from the compute nodes, you will need to [[Technical support|contact our technical support]] so that we can configure our firewall(s) to permit the software to connect to your licence server.

If you are a PI holding the Materials Studio licence, you can install Materials Studio once so those working under you can use that installation. Since normally team work is stored in <code>/project</code> space, determine which project directory you want to use. Suppose it is <code>~/projects/A_DIRECTORY</code>, then you'll need to know these two values:

1. Determine the actual path of A_DIRECTORY as follows: {{Commands|PI_PROJECT_DIR{{=}}$(readlink -f ~/projects/A_DIRECTORY)|echo $PI_PROJECT_DIR}}

2. Determine the group of A_DIRECTORY as follows: {{Commands|PI_GROUP{{=}}$(stat -c%G $PI_PROJECT_DIR)|echo $PI_GROUP}}

With these values known, install Materials Studio as follows:

# Change your default group to your team's <code>def-</code> group, e.g., {{Command|newgrp $PI_GROUP}}

# Open the permissions of your project directory so your team can access it, e.g., {{Command|chmod g+rsx $PI_PROJECT_DIR}}

# Install the software, e.g., {{Command|MS_LICENSE_SERVER{{=}}<port>@<server> eb MaterialsStudio-2018-dummy-dummy.eb --installpath{{=}}$PI_PROJECT_DIR/MatStudio2018 --sourcepath{{=}}$HOME}}

Before the software can be run, the following must be run first:

# Load the module information for the installed software, e.g., {{Command|module use $PI_PROJECT_DIR/MatStudio2018/modules/2017/Core/}}

#* Your team members may wish to add this to their <code>~/.bashrc</code> file.

# Optional: If you want files to be written readable by group members, change your default group to the team <code>def-</code> group, e.g., {{Command|newgrp $PI_GROUP}}

'''NOTE:''' In any scripts, etc. used, be sure to replace the above PI_GROUP and PI_PROJECT_DIR variables with what their values are.

The examples below assume that you have installed Materials Studio 2018 according to the instructions above.  

{{File|contents=

#!/bin/bash

#SBATCH --nodes=1

#SBATCH --time=12:00:00

module load materialsstudio/2018

# Create a list of nodes to be used for the job

DSD_MachineList="machines.LINUX"

export DSD_MachineList

# Job to run

RunDMol3.sh -np $SLURM_CPUS_PER_TASK Brucite001f

{{File|contents=

#!/bin/bash

#SBATCH --nodes=1

#SBATCH --time=0-12:00

module load materialsstudio/2018

DSD_MachineList="mpd.hosts"

slurm_hl2hl.py --format MPIHOSTLIST >$DSD_MachineList

export DSD_MachineList

RunCASTEP.sh -np $SLURM_CPUS_PER_TASK castepjob

if [ -f castepjob_NMR.param ]; then

   cp castepjob.check castepjob_NMR.check

}}

If you require using an earlier version of Materials Studio than 2018, you will need to install in into a [[Singularity]] container. This involves:

# Creating a Singularity container with a compatible distribution of Linux installed in it.