SSH keys allow a user on a local computer/client to log in to a remote SSH server without having to enter a password. This method of user authentication is preferred over traditional password authentication for the following reasons.

• Your passwords won’t be transmitted over insecure networks where they could be intercepted or cracked
• Brute-force password attacks by outsiders won’t work on a system that doesn’t accept passwords
• Users won’t have to enter their passwords to log in every time. That’s very convenient from users’ point of view.
• Once you have set up your SSH keys, other secure shell services relying on openSSH such as rsync, sftp, scp, ... will be able to work without passwords as well.

Two words of caution first:

• You would only need to set up SSH keys once per local computer per user. The local computer needs to be a personal laptop/desktop, but a research group workstation is acceptable although not encouraged. 
• Please do not set up SSH keys on public or non-research computers. This includes shared computers in public spaces like libraries, internet cafés, … etc. It also includes computers owned by friends and family (your parents, grandparents, boyfriend/girlfriend, BFFs … etc). If such an activity is detected, your account will be deactivated immediately.

To access Marcy/Skylight using SSH keys from your local computer, you first need to generate a public-private SSH key pair on your local computer, then transmit the public key to Marcy/Skylight.  

Here are instructions on how to do that.  The instructions assume you are on a Mac or Linux machine.

1. Check if you already have SSH keys on your local machine. SSH keys are generally saved at ~/.ssh directory.
   •  Enter ‘ls ~/.ssh‘. If you see files named ‘id_rsa‘ and ‘id_rsa.pub‘, move to Step 2 to copy the SSH keys.
     • username@local-machine|~/> ls ~/.ssh
authorized_keys   id_rsa    id_rsa.pub    known_hosts
   • If ~/.ssh does not exist or contain ‘id_rsa‘ and ‘id_rsa.pub‘, move to Step 3 to generate new SSH keys 
     • username@local-machine|~/> ls ~/.ssh
        
2. Copy SSH keys: You already have SSH keys on your local computer and you will just need to copy them to Marcy/Skylight.
   • Copy the SSH key to Marcy.
     username@local-machine|~/> cat ~/.ssh/id_rsa.pub | ssh username@marcy.furman.edu 'cat >> .ssh/authorized_keys'
   • Log into Marcy and copy the key to Skylight.
     username@local-machine|~/> ssh username@marcy.furman.edu
username@marcy|~/> tail -n 1 ~/.ssh/authorized_keys | ssh skylight 'cat >> ~/.ssh/authorized_keys'
3. Generate and copy SSH keys: 
   • Generate an SSH key on your local computer
     username@local-machine|~/> ssh-keygen -b 1024 -t rsa -N ""
     That should generate a public-private key pair and save it ~/.ssh. Check to make sure it is there.
     username@local-machine|~/> ls ~/.ssh
authorized_keys  id_rsa    id_rsa.pub    known_hosts

   • Copy the key to Marcy.
     username@local-machine|~/> cat ~/.ssh/id_rsa.pub | ssh username@marcy.furman.edu 'cat >> .ssh/authorized_keys'
   • Log into Marcy and copy the key to Skylight.
     username@local-machine|~/> ssh username@marcy.furman.edu
username@marcy|~/> tail -n 1 ~/.ssh/authorized_keys | ssh skylight 'cat >> ~/.ssh/authorized_keys'
4. Test: you should be all set to SSH to Skylight and Marcy using SSH keys. Try logging in.
   • ssh username@marcy.furman.edu
   • ssh username@skylight.furman.edu


     If you have any questions or encounter any problems, please email support@mercuryconsortium.org

Once you have set up your SSH keys, other secure shell services relying on openSSH such as rsync, sftp, scp, ... will be able to work without passwords as well. If you use file transfer applications like CyberDuck or Filezilla, they should know where to look for your keys. If you have any trouble, please email support@mercuryconsortium.org.

The cluster has a lot of software stored in /usr/local/Dist and more will be added as necessary. Some essential software and environments are set at login. but the vast majority of the scientific software is provisioned using the Modules software environment management tool. When you load a specific application module, the proper environmental variables, dependencies and paths that are needed to execute that application are set and provided for you. The most recent version(s) of commonly used applications in computational chemistry are compiled to run optimally on Skylight and and provided as modules. If you need other applications or older versions of these applications, please send a request to support@mercuryconsortium.org and we will do our best to make them available to you quickly.

1. Gaussian16 A.03
2. Gaussian09 A.02 + D.03
3. Orca 3.0.3 + 4.0.0
4. GAMESS 2016
5. AMBER 12, 14
6. AMBER 16 w/ GPU support for both NVIDIA GTX 1080 and P100 cards
7. LAMMPS 03-31-2017 
8. NAMD 2.12 w/ GPU support
9. CP2K 2.6 + 3.0 + 4.1 
10. Desmond 2016
11. libEFP

1. NWchem
2. PSI4
3. CFOUR
4. GROMACS
5. OpenMM
6. Quantum Espresso
7. Siesta
8. CPMD
9. DFTB+
10. cluster 

1. Intel Compilers (16, 17)
2. Intel MKL libraries (16, 17)
3. Intel MPI (17)
4. GCC (4.8.5)
5. OpenMPI (1.6, 1.8, 2.0)
6. MVAPICH2 (2.2)
7. MPICH (3.3)
8. Python (2.7.5, 3.3)

The next example demonstrates the use of modules to set up one’s environment to do a GPU calculation using AMBER16

user@master[~] module list
Currently Loaded Modulefiles:
 1) null 2) modules 3) use.own

You can execute module avail to see available modules and get documentation about running these modules through module show module_name

user@master[~] module avail

--------------------- /usr/local/Modules/modulefiles ----------------------------------------------------------------------------------
amber/12            cpmd/3.17.1         gamess/default      module-info         psi4/07-13
amber/14            cpmd/default        gaussian/default    modules             psi4/default
amber/16            cuda/6.0            gaussian/g09-A02    namd/2.12-ib        psi4/miniconda
amber/16-cuda       cuda/8.0            gaussian/g09-D01    namd/2.12-ib-cuda   python/2.7.13
amber/default       cuda/default        gaussian/g16-A03    namd/2.12-omp       python/2.7-intel
cfour/1.0           desmond/2016-4      gromacs/5.0-beta    namd/default        python/3.3.0
cluster/1.2         dftb+/1.2.2-mpi     InVEST              null                qe/6.1
cluster/1.3         dftb+/1.2.2-serial  lammps/3-2017       nwchem/6.3          scalapack/2.0.2-gnu
cluster/default     dock6/6.7           libefp/1.4.2        nwchem/6.5          siesta/3.2
cp2k/2.6.2          dot                 miniconda/psi4      nwchem/6.6          use.own
cp2k/3.0            espresso/5.1        mlpr/2015.1.14      nwchem/default
cp2k/4.1            fftw/3.3.3          mlpr/default        openmm/5.4
cp2k/default        gamess/2016         module-git          openmm/6.1

-------------------------- /home/user/privatemodules --------------------------------------------------------------------------------------- 
null 

user@master[~] module show gamess/2016

-------------------------------------------------------------------
/usr/local/Modules/modulefiles/gamess/2016:

module-whatis Adds `/usr/local/Dist/gamess/16' to your 'PATH/LD_LIBRARY/MANPATH' environment
module-whatis To run Gamess calculations, use the rungamess.csh script.
module-whatis Usage: rungms inputfile ScratchDirName NumberOfProcesses/CoresToUse
module-whatis Eg: rungms test.inp myScrDir 16

module-whatis Eg: rungms exam01.inp $SLURM_JOB_ID  $SLURM_NTASKS

module-whatis Or adapt the script (/usr/local/Dist/bin/rungamess-16.csh for your purposes.

module load intel impi
prepend-path PATH /usr/local/Dist/gamess/16
-------------------------------------------------------------------

Slurm Job Scheduler

Unlike our past HPC systems where we used SunGridEngine (SGE) or Torque(OpenPBS)+Maui for job scheduling, we have switched to Slurm for Skylight. From users’ standpoint, Slurm looks very much like the familiar PBS, except with #SBATCH instead of #PBS directives. For a quick overview of Slurm, please visit this page.

 

Here are some common Slurm commands and their description:

The table below shows a summary of SLURM commands. These commands are described in more detail below along with links to the SLURM doc site.

	SLURM	SLURM Example
Submit a batch job	sbatch	sbatch run.slurm
Run a script interatively	srun	srun --pty -p interact -t 10 --mem 1000 /bin/bash /bin/run.csh
Kill a job	scancel	scancel 1542
View status of queues	squeue	squeue -u username

#!/bin/tcsh
#SBATCH -p stdmem                   # Queue/Partition to submit to
#SBATCH -n 20                       # Number of cores or tasks per node (--ntasks-per-node=20)
#SBATCH -N 1                        # Number of nodes (--nodes=1) ;should be 1 in most cases)
#SBATCH -t 48:00:00                 # Runtime in D-HH:MM:SS
#SBATCH --mem=100G                  # Total Memory needed for all cores (see also --mem-per-cpu)
#SBATCH -o jTest_%j.err             # File to which STDOUT & STDERR will be written
#SBATCH --job-name="jTest"          # Job name that will appear in the queue
#SBATCH --mail-type=END             # Type of email notification- BEGIN,END,FAIL,ALL
#SBATCH --mail-user=user@host.edu   # Email to which notifications will be sent

source /usr/share/Modules/init/tcsh              #necessary to make sure modules work in TCSH shell
set echo

module load gaussian/g16-A03                     #Load the right Gaussian module
setenv GAUSS_SCRDIR /scratch/$GROUP/$USER        #Optionally set scratch directory path
g16 test.com                                     #Run a test calculation

The easiest way to learn how to run calculations is to look at the examples provided below. The Slurm batch submission files are named run.slurm and all the input and output files from the particular calculation are also provided in the same directory. Good luck and happy computing!