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Revision as of 18:01, 23 July 2009 by Kilian (talk | contribs)
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General Information

home directory quota

There is a 10GB quota limit enforced on $HOME directory (/global/home/users/username) usage. Please keep your usage below this limit. There will NETAPP snapshots in place in this file system so we suggest you store only your source code and scripts in this area and store all your data under /clusterfs/cortex (see below).


For large amounts of data, please create a directory


and store the data inside that directory.


get a password

  • press the PASS WORD button on your crypto card
  • enter passoword
  • press enter
  • the 7 digit password is given (without the dash)

setup environment

  • put all your customizations into your .bashrc
  • for login shells, .bash_profile is used, which in turn loads .bashrc

ssh to the gateway computer (hadley)

note: please don't use the gateway for computations (e.g. matlab)!

 ssh -Y (or 

and use your crypto password

Useful commands

Start interactive session on compute node

  • start interactive session:
 qsub -X -I
  • start interactive session on particular node (nodes n0000.cortex and n0001.cortex have GPUs):
 qsub -X -I -l nodes=n0001.cortex

Perceus commands

The perceus manual is here

  • listing available cluster nodes:
  • list cluster usage
  • to restrict the scope of these commands to cortex cluster, add the following line to your .bashrc
 export NODES='*cortex'
  • module list
  • module avail
  • module help

Resource Manager PBS

  • Job Scheduler MOAB
  • List running jobs:
 qstat -a
  • List jobs of a given node:
 qstat -n 98
  • sample script
 #PBS -q cortex
 #PBS -l nodes=1:ppn=2:cortex
 #PBS -l walltime=01:00:00
 #PBS -o path-to-output
 #PBS -e path-to-error
 cd /global/home/users/kilian/sample_executables
 mpirun -np 8 /bin/hostname
 sleep 60
  • submit script
 qsub scriptname
  • interactive session
 qsub -I -q cortex -l nodes=1:ppn=2:cortex -l walltime=00:15:00
  • list nodes that your job is running on
  • run the program on several cores
 mpirun -np 4 -mca btl ^openib sample_executables/mpi_hello


note: remember to start an interactive session before starting matlab!

In order to use matlab, you have to load the matlab environment:

 module load matlab

Once the matlab environment is loaded, you can start a matlab session by running

 matlab -nojvm -nodesktop


We have the Source Python Distribution installed [SPD]. In order to use python with ipython/numpy/scipy, you have to first load the python environment module:

 module load python/spd

Afterwards, you can run ipython

 % ipython -pylab

At the moment, we have numpy, scipy, and matplotlib installed. If you would like to have additional modules installed, let me know [kilian]


Sage is In order to use sage, you have to first load the sage environment module

 module load python/sage

After loading the sage module, if you want to have a scipy environment (run ipython, etc) in your interactive session, first do:

 % sage -sh

then you can run:

 % ipython

or you can just do:

 % sage -ipython

This is a temporary solution for people wanting use scipy with mpi on the cluster. It was built against the default openmpi (1.2.8) (icc) and mpi4py 1.1.0. For those using hdf5, I also built hdf5 1.8.3 (gcc) and h5py 1.2.

Sample pbs and mpi script is here:


You can run it as:

 % mkdir -p ~/jobs
 % cd ~amirk/test
 % qsub pbs



I've installed CUDA 2.2 toolkit here:


The SDK is here:


To your PATH, add:


To your LD_LIBRARY_PATH, add:



Support Requests

  • If you have a problem that is not covered on this page, you can send an email to our user list:
  • If you need additional help from the LBL group, send an email to their email list. Please always cc our email list as well.
  • In urgent cases, you can also email Krishna Muriki (LBL User Services) directly.