This cluster is dedicated to large shared-memory jobs (100+ GB of RAM and 24+ cores).
Here is an example of a configuration .ac file:
with_mpi_prefix="/home/ucl/naps/ygillet/tools/openmpi-1.6.3-gcc-4.7.2" enable_64bit_flags="yes" enable_mpi="yes" enable_mpi_io="yes" enable_gw_dpc="yes" with_fft_flavor="fftw3" with_fft_libs="-L/opt/intel/compilerpro-12.0.0.084/mkl/lib/intel64 -Wl,--start-group -lmkl_gf_lp64 -lmkl_sequential -lmkl_core -Wl,--end-group -lpthread -lm" with_linalg_flavor="mkl" with_linalg_libs="-L/opt/intel/compilerpro-12.0.0.084/mkl/lib -Wl,--start-group -lmkl_gf_lp64 -lmkl_sequential -lmkl_core -Wl,--end-group -lpthread -lm"
HMEM use a Slurm submission script system.
Here is an example submission script (you have to modify it slightly to suit your need):
#!/bin/bash #SBATCH --job-name=your_job_name #SBATCH --mail-user=your_e_mail@blabla.com #SBATCH --mail-type=ALL #SBATCH --time=90:00:00 #SBATCH --ntasks=30 ####SBATCH --ntasks-per-node=16 #SBATCH --cpus-per-task=1 ####SBATCH --partition=High #SBATCH --mem-per-cpu=5000 module purge module load gcc source /usr/local/intel/compilerpro-12.0.0.084/mkl/bin/mklvars.sh intel64 export PATH=$PATH:/home/ucl/naps/ygillet/tools/openmpi-1.6.3-gcc-4.7.2/bin export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/home/ucl/naps/ygillet/tools/openmpi-1.6.3-gcc-4.7.2/lib export OMP_NUM_THREADS=1 unset SLURM_CPUS_PER_TASK MPIRUN="mpirun" MPIOPT="--mca btl tcp,self -n 2" ABINIT="/home/ucl/naps/sponce/Develop/7.2.0-private/build/src/98_main/abinit" ${MPIRUN} ${MPIOPT} ${ABINIT} < sigma10.files >& logsigma10_DS4 echo "--"