#!/bin/bash #PBS -P j23 #PBS -q normal #PBS -l walltime=120,ncpus=4,vmem=400mb,other=mpi #PBS -wd ######################### # The above #PBS directives do the following: ######################### # #PBS -P j23 # Set the project to be charged to be j23 # # #PBS -q normal # Run this job in the normal queue # # #PBS -l walltime=120,ncpus=4,vmem=400mb,other=mpi # This job will not take longer than 120 seconds. # This job requires 4 processors. # This job will not consume more than 400mb. # This job requires MPI. # # #PBS -wd # Start the job in the directory it was submitted from. # (This script must be submitted from the ga/inundation/parallel directory) # ######################### ######################### # The APAC cluster uses modules to customise the user's environment. # Python and LAM-MPI are required for this job. MPICH will not work, because it # cannot pass the PYTHONPATH environment variable into the mpi job. ######################### module load python module load lam ######################### # As with a standard ANUGA installation, PYTHONPATH must be correctly set. # The job will fail strangely on the APAC Linux Cluster if LD_ASSUME_KERNEL # is not set. This is not required on other machines. ######################### export PYTHONPATH=/home/661/jdk661/inundation export LD_ASSUME_KERNEL=2.4.1 ######################### # Start the actual MPI job on 4 nodes. # Ensure that the MPI environment has the LD_LIBRARY_PATH (used because the # modular environment places some libraries in nonstandard locations), # PYTHONPATH and LD_ASSUME_KERNEL environment variables set correctly. ######################### lamboot mpirun -np 4 -x LD_LIBRARY_PATH,PYTHONPATH,LD_ASSUME_KERNEL run_parallel_sw_merimbula_metis.py lamhalt