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---
title: ANSYS / MAPDL
#tags:
last_updated: 30 June 2020
keywords: software, ansys, mapdl, slurm, apdl
summary: "This document describes how to run ANSYS/Mechanical APDL in the Merlin6 cluster"
sidebar: merlin6_sidebar
permalink: /merlin6/ansys-mapdl.html
---
This document describes the different ways for running **ANSYS/Mechanical APDL**
## ANSYS/Mechanical APDL
Is always recommended to check which parameters are available in Mechanical APDL and adapt the below examples according to your needs.
For that, please refer to the official Mechanical APDL documentation.
## Running Mechanical APDL jobs
### PModules
Is strongly recommended the use of the latest ANSYS software **ANSYS/2020R1-1** available in PModules.
```bash
module use unstable
module load ANSYS/2020R1-1
```
### Non-interactive: sbatch
Running jobs with `sbatch` is always the recommended method. This makes the use of the resources more efficient. Notice that for
running non interactive Mechanical APDL jobs one must specify the `-b` option.
#### Serial example
This example shows a very basic serial job.
```bash
#!/bin/bash
#SBATCH --job-name=MAPDL # Job Name
#SBATCH --partition=hourly # Using 'daily' will grant higher priority than 'general'
#SBATCH --time=0-01:00:00 # Time needed for running the job. Must match with 'partition' limits.
#SBATCH --cpus-per-task=1 # Double if hyperthreading enabled
#SBATCH --ntasks-per-core=1 # Double if hyperthreading enabled
#SBATCH --hint=nomultithread # Disable Hyperthreading
#SBATCH --error=slurm-%j.err # Define your error file
module use unstable
module load ANSYS/2020R1-1
# [Optional:BEGIN] Specify your license server if this is not 'lic-ansys.psi.ch'
LICENSE_SERVER=<your_license_server>
export ANSYSLMD_LICENSE_FILE=1055@$LICENSE_SERVER
export ANSYSLI_SERVERS=2325@$LICENSE_SERVER
# [Optional:END]
SOLVER_FILE=/data/user/caubet_m/MAPDL/mysolver.in
mapdl -b -i "$SOLVER_FILE"
```
One can enable hypertheading by defining `--hint=multithread`, `--cpus-per-task=2` and `--ntasks-per-core=2`.
However, this is in general not recommended, unless one can ensure that can be beneficial.
#### SMP-based example
This example shows how to running Mechanical APDL in Shared-Memory Parallelism mode. It limits the use
to 1 single node, but by using many cores. In the example below, we use a node by using all his cores
and the whole memory.
```bash
#!/bin/bash
#SBATCH --job-name=MAPDL # Job Name
#SBATCH --partition=hourly # Using 'daily' will grant higher priority than 'general'
#SBATCH --time=0-01:00:00 # Time needed for running the job. Must match with 'partition' limits.
#SBATCH --nodes=1 # Number of nodes
#SBATCH --ntasks=1 # Number of tasks
#SBATCH --cpus-per-task=44 # Double if hyperthreading enabled
#SBATCH --hint=nomultithread # Disable Hyperthreading
#SBATCH --error=slurm-%j.err # Define a file for standard error messages
#SBATCH --exclusive # Uncomment if you want exclusive usage of the nodes
module use unstable
module load ANSYS/2020R1-1
# [Optional:BEGIN] Specify your license server if this is not 'lic-ansys.psi.ch'
LICENSE_SERVER=<your_license_server>
export ANSYSLMD_LICENSE_FILE=1055@$LICENSE_SERVER
export ANSYSLI_SERVERS=2325@$LICENSE_SERVER
# [Optional:END]
SOLVER_FILE=/data/user/caubet_m/MAPDL/mysolver.in
mapdl -b -np ${SLURM_CPUS_PER_TASK} -i "$SOLVER_FILE"
```
In the above example, one can reduce the number of **cpus per task**. Here usually `--exclusive`
is recommended if one needs to use the whole memory.
For **SMP** runs, one might try the hyperthreading mode by doubling the proper settings
(`--cpus-per-task`), in some cases it might be beneficial.
Please notice that `--ntasks-per-core=1` is not defined here, this is because we want to run 1
task on many cores! As an alternative, one can explore `--ntasks-per-socket` or `--ntasks-per-node`
for fine grained configurations.
#### MPI-based example
This example enables Distributed ANSYS for running Mechanical APDL using a Slurm batch script.
```bash
#!/bin/bash
#SBATCH --job-name=MAPDL # Job Name
#SBATCH --partition=hourly # Using 'daily' will grant higher priority than 'general'
#SBATCH --time=0-01:00:00 # Time needed for running the job. Must match with 'partition' limits.
#SBATCH --nodes=1 # Number of nodes
#SBATCH --ntasks=44 # Number of tasks
#SBATCH --cpus-per-task=1 # Double if hyperthreading enabled
#SBATCH --ntasks-per-core=1 # Run one task per core
#SBATCH --hint=nomultithread # Disable Hyperthreading
#SBATCH --error=slurm-%j.err # Define a file for standard error messages
##SBATCH --exclusive # Uncomment if you want exclusive usage of the nodes
module use unstable
module load ANSYS/2020R1-1
# [Optional:BEGIN] Specify your license server if this is not 'lic-ansys.psi.ch'
LICENSE_SERVER=<your_license_server>
export ANSYSLMD_LICENSE_FILE=1055@$LICENSE_SERVER
export ANSYSLI_SERVERS=2325@$LICENSE_SERVER
# [Optional:END]
SOLVER_FILE=input.dat
# INTELMPI=no for IBM MPI
# INTELMPI=yes for INTEL MPI
INTELMPI=no
if [ "$INTELMPI" == "yes" ]
then
# When using -mpi=intelmpi, KMP Affinity must be disabled
export KMP_AFFINITY=disabled
# INTELMPI is not aware about distribution of tasks.
# - We need to define tasks distribution.
HOSTLIST=$(srun hostname | sort | uniq -c | awk '{print $2 ":" $1}' | tr '\n' ':' | sed 's/:$/\n/g')
mapdl -b -dis -mpi intelmpi -machines $HOSTLIST -np ${SLURM_NTASKS} -i "$SOLVER_FILE"
else
# IBMMPI (default) will be aware of the distribution of tasks.
# - In principle, no need to force tasks distribution
mapdl -b -dis -mpi ibmmpi -np ${SLURM_NTASKS} -i "$SOLVER_FILE"
fi
```
In the above example, one can increase the number of *nodes* and/or *ntasks* if needed and combine it
with `--exclusive` when necessary. In general, **no hypertheading** is recommended for MPI based jobs.
Also, one can combine it with `--exclusive` when necessary.