Content
Code Compilation
For code compilation you can choose one of the two compilers - Intel oneAPI or GNU. Both compilers are able to include the Intel MPI library.
Intel one API compiler
module load intel
module load impi
mpiicx -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.c
mpiifx -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.f90
mpiicpx -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.cpp
module load intel
module load impi
mpiicx -fopenmp -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.c
mpiifx -fopenmp -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.f90
mpiicpx -fopenmp -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.cpp
GNU compiler
module load gcc
module load impi
mpigcc -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.c
mpif90 -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.f90
mpigxx -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.cpp
module load gcc
module load impi
mpigcc -fopenmp -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.c
mpif90 -fopenmp -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.f90
mpigxx -fopenmp -Wl,-rpath,$LD_RUN_PATH -o hello.bin hello.cpp
Slurm job script
You need to start the MPI parallelized code on the system. You can choose between
- using
mpirun
and - using
srun
.
Using mpirun
Using mpirun
the pinning is controlled by the MPI library. Pinning by SLURM you need to switch off by adding export SLURM_CPU_BIND=none
.
MPI only
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
mpirun -ppn 96 ./hello.bin
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
export I_MPI_PIN_DOMAIN=core
export I_MPI_PIN_ORDER=scatter
mpirun -ppn 48 ./hello.bin
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
mpirun -ppn 192 ./hello.bin
MPI, OpenMP
You can run one code compiled with MPI and OpenMP. The examples cover the setup
- 2 nodes,
- 4 processes per node, 24 threads per process.
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
export OMP_NUM_THREADS=24
mpirun -ppn 4 ./hello.bin
The example covers the setup
- 2 nodes,
- 4 processes per node, 12 threads per process.
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=12
mpirun -ppn 4 ./hello.bin
The example covers the setup
- 2 nodes,
- 4 processes per node using hyperthreading,
- 48 threads per process.
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
module load impi/2019.5
export SLURM_CPU_BIND=none
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=48
mpirun -ppn 4 ./hello.bin
Using srun
MPI only
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
srun --ntasks-per-node=96 ./hello.bin
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
srun --ntasks-per-node=48 ./hello.bin
MPI, OpenMP
You can run one code compiled with MPI and OpenMP. The example covers the setup
- 2 nodes,
- 4 processes per node, 24 threads per process.
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=24
srun --ntasks-per-node=4 --cpus-per-task=48 ./hello.bin
The example covers the setup
- 2 nodes,
- 4 processes per node, 12 threads per process.
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=12
srun --ntasks-per-node=4 --cpus-per-task=24 ./hello.bin
The example covers the setup
- 2 nodes,
- 4 processes per node using hyperthreading,
- 48 threads per process.
#!/bin/bash
#SBATCH --nodes=2
#SBATCH --partition=standard96:test
export OMP_PROC_BIND=spread
export OMP_NUM_THREADS=48
srun --ntasks-per-node=4 --cpus-per-task=48 ./hello.bin