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#!/bin/bash
#SBATCH -t 00:59:00
#SBATCH --nodes=1
#SBATCH --partition=gpu-a100:shared
#SBATCH --ntasks-per-node=1
#SBATCH --gres=gpu:1             # number of GPUs per node - ignored if exclusive partition with 4 GPUs
#SBATCH --gpu-bind=single:1      # bind each process to its own GPU (single:<tasks_per_gpu>)
#SBATCH -L ansys
#SBATCH --output="slurm-log.%j"

module add gcc openmpi/gcc.11 ansys/2023r2_mlx_openmpiCUDAaware # external OpenMPI is CUDA-aware
hostlist=$(srun hostname -s | sort | uniq -c | awk '{printf $2":"$1","}')
echo "Running on nodes: $hostlist"

cat <<EOF > tui>tui_input.jou
file/read-cas nozzle_gpu_supported.cas.h5
solve/initialize/hyb-initialization
solve/iterate 1000 yes
file/write-case-data outputfile1
file/export cgns outputfile2 full-domain yes yes
pressure temperature x-velocity y-velocity mach-number
quit
exit
EOF

fluent 3ddp -g -cnf=$hostlist -t${SLURM_NTASKS} -gpu -nm -i tui_input.jou \
       -mpi=openmpi -pib -mpiopt="--report-bindings --rank-by core" >/dev/null 2>&1
echo '#################### Fluent finished ############'

#!/bin/bash
#SBATCH -t 00:10:00
#SBATCH --nodes=2
#SBATCH --ntasks-per-node=4
#SBATCH -L ansys
#SBATCH -p gpu-a100
### on emmy -p is simply called gpu
#SBATCH --output="slurm.log.%j"
#SBATCH --job-name=cavity_on_gpu

echo "Running on nodes: ${SLURM_JOB_NODELIST}"
srun hostname -s > hostfile

module add gcc openmpi/gcc.11 # external OpenMPI is CUDA aware
module add ansys/2023r2_mlx_openmpiCUDAaware

cat <<EOF > fluent>fluent.jou
; this is an Ansys journal file aka text user interface (TUI) file
parallel/gpgpu/show
file/read-case initial_run.cas.h5
solve/iterate 100
file/write-case-data outputfile
ok
exit
EOF

fluent 2d -g -t${SLURM_NTASKS} -gpgpu=4 -mpi=openmpi -pib -cnf=hostfile -i fluent.jou  >/dev/null 2>&1
echo '#################### Fluent finished ############'