Updated: 22 December 2023
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For other version, check https://github.com/MPAS-Dev/MPAS-Model/releases. |
3. Compile MPAS
Compile each MPAS core
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with your desired floating-point precision; for example,
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make -j4 intel-nersc CORE=init_atmosphere PRECISION=single AUTOCLEAN=true make -j4 intel-nersc CORE=atmosphere PRECISION=single AUTOCLEAN=true ... |
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Additional notes:
CORE=ocean only supports double precision.
CORE=seaice only supports double precision and only serial build (-j1) works.
Users may have to add parentheses for the print function, i.e., print xxx → print(xxx), in
./src/core_ocean/BGC/makedep.py
./src/core_ocean/cvmix/makedep.py
to make these files compatible with Python3.
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#!/bin/bash
#SBATCH -p compute # Partition
#SBATCH -N 1 # Number of nodes
#SBATCH --ntasks-per-node=64 # Number of MPI processes per node
#SBATCH --cpus-per-task=2 # Number of OpenMP threads per MPI process
#SBATCH -t 5-00:00:00 # Job runtime limit
#SBATCH -J MPAS # Job name
#SBATCH -A ltxxxxxx # Account *** {USER EDIT} ***
module purge
module load ParallelIO/2.6.2-cpeIntel-23.09
module load METIS/5.1.0-cpeIntel-23.09
export OMP_STACKSIZE="32M"
export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}
ulimit -s unlimited
srun -n${SLURM_NTASKS} -c${SLURM_CPUS_PER_TASK} ./init_atmosphere_model
srun -n${SLURM_NTASKS} -c${SLURM_CPUS_PER_TASK} ./atmosphere_model
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MPAS static geographical datasets are available at Users can choose one of them as |
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Contact Us
ThaiSC support service : thaisc-support@nstda.or.th
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