163 lines
6.3 KiB
Markdown
163 lines
6.3 KiB
Markdown
---
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title: ANSYS / MAPDL
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#tags:
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keywords: software, ansys, mapdl, slurm, apdl, interactive, rsm, batch job
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last_updated: 07 September 2022
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summary: "This document describes how to run ANSYS/Mechanical APDL in the Merlin6 cluster"
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sidebar: merlin6_sidebar
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permalink: /merlin6/ansys-mapdl.html
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---
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This document describes the different ways for running **ANSYS/Mechanical APDL**
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## ANSYS/Mechanical APDL
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Is always recommended to check which parameters are available in Mechanical APDL and adapt the below examples according to your needs.
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For that, please refer to the official Mechanical APDL documentation.
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## Running Mechanical APDL jobs
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### PModules
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Is strongly recommended the use of the latest ANSYS software available in PModules.
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```bash
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module use unstable
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module load Pmodules/1.1.6
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module use overlay_merlin
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module load ANSYS/2022R1
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```
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### Interactive: RSM from remote PSI Workstations
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Is possible to run Mechanical through RSM from remote PSI (Linux or Windows) Workstation having a local installation of ANSYS Mechanical and RSM client.
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For that, please refer to the ***[ANSYS RSM]*(/merlin6/ansys-rsm.html)** in the Merlin documentation for further information of how to setup a RSM client for submitting jobs to Merlin.
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### Non-interactive: sbatch
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Running jobs with `sbatch` is always the recommended method. This makes the use of the resources more efficient. Notice that for
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running non interactive Mechanical APDL jobs one must specify the `-b` option.
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#### Serial example
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This example shows a very basic serial job.
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```bash
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#!/bin/bash
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#SBATCH --job-name=MAPDL # Job Name
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#SBATCH --partition=hourly # Using 'daily' will grant higher priority than 'general'
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#SBATCH --time=0-01:00:00 # Time needed for running the job. Must match with 'partition' limits.
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#SBATCH --cpus-per-task=1 # Double if hyperthreading enabled
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#SBATCH --ntasks-per-core=1 # Double if hyperthreading enabled
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#SBATCH --hint=nomultithread # Disable Hyperthreading
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#SBATCH --error=slurm-%j.err # Define your error file
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module use unstable
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module load ANSYS/2020R1-1
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# [Optional:BEGIN] Specify your license server if this is not 'lic-ansys.psi.ch'
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LICENSE_SERVER=<your_license_server>
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export ANSYSLMD_LICENSE_FILE=1055@$LICENSE_SERVER
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export ANSYSLI_SERVERS=2325@$LICENSE_SERVER
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# [Optional:END]
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SOLVER_FILE=/data/user/caubet_m/MAPDL/mysolver.in
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mapdl -b -i "$SOLVER_FILE"
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```
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One can enable hypertheading by defining `--hint=multithread`, `--cpus-per-task=2` and `--ntasks-per-core=2`.
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However, this is in general not recommended, unless one can ensure that can be beneficial.
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#### SMP-based example
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This example shows how to running Mechanical APDL in Shared-Memory Parallelism mode. It limits the use
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to 1 single node, but by using many cores. In the example below, we use a node by using all his cores
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and the whole memory.
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```bash
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#!/bin/bash
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#SBATCH --job-name=MAPDL # Job Name
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#SBATCH --partition=hourly # Using 'daily' will grant higher priority than 'general'
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#SBATCH --time=0-01:00:00 # Time needed for running the job. Must match with 'partition' limits.
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#SBATCH --nodes=1 # Number of nodes
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#SBATCH --ntasks=1 # Number of tasks
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#SBATCH --cpus-per-task=44 # Double if hyperthreading enabled
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#SBATCH --hint=nomultithread # Disable Hyperthreading
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#SBATCH --error=slurm-%j.err # Define a file for standard error messages
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#SBATCH --exclusive # Uncomment if you want exclusive usage of the nodes
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module use unstable
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module load ANSYS/2020R1-1
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# [Optional:BEGIN] Specify your license server if this is not 'lic-ansys.psi.ch'
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LICENSE_SERVER=<your_license_server>
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export ANSYSLMD_LICENSE_FILE=1055@$LICENSE_SERVER
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export ANSYSLI_SERVERS=2325@$LICENSE_SERVER
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# [Optional:END]
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SOLVER_FILE=/data/user/caubet_m/MAPDL/mysolver.in
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mapdl -b -np ${SLURM_CPUS_PER_TASK} -i "$SOLVER_FILE"
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```
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In the above example, one can reduce the number of **cpus per task**. Here usually `--exclusive`
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is recommended if one needs to use the whole memory.
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For **SMP** runs, one might try the hyperthreading mode by doubling the proper settings
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(`--cpus-per-task`), in some cases it might be beneficial.
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Please notice that `--ntasks-per-core=1` is not defined here, this is because we want to run 1
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task on many cores! As an alternative, one can explore `--ntasks-per-socket` or `--ntasks-per-node`
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for fine grained configurations.
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#### MPI-based example
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This example enables Distributed ANSYS for running Mechanical APDL using a Slurm batch script.
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```bash
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#!/bin/bash
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#SBATCH --job-name=MAPDL # Job Name
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#SBATCH --partition=hourly # Using 'daily' will grant higher priority than 'general'
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#SBATCH --time=0-01:00:00 # Time needed for running the job. Must match with 'partition' limits.
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#SBATCH --nodes=1 # Number of nodes
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#SBATCH --ntasks=44 # Number of tasks
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#SBATCH --cpus-per-task=1 # Double if hyperthreading enabled
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#SBATCH --ntasks-per-core=1 # Run one task per core
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#SBATCH --hint=nomultithread # Disable Hyperthreading
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#SBATCH --error=slurm-%j.err # Define a file for standard error messages
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##SBATCH --exclusive # Uncomment if you want exclusive usage of the nodes
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module use unstable
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module load ANSYS/2020R1-1
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# [Optional:BEGIN] Specify your license server if this is not 'lic-ansys.psi.ch'
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LICENSE_SERVER=<your_license_server>
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export ANSYSLMD_LICENSE_FILE=1055@$LICENSE_SERVER
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export ANSYSLI_SERVERS=2325@$LICENSE_SERVER
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# [Optional:END]
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SOLVER_FILE=input.dat
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# INTELMPI=no for IBM MPI
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# INTELMPI=yes for INTEL MPI
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INTELMPI=no
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if [ "$INTELMPI" == "yes" ]
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then
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# When using -mpi=intelmpi, KMP Affinity must be disabled
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export KMP_AFFINITY=disabled
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# INTELMPI is not aware about distribution of tasks.
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# - We need to define tasks distribution.
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HOSTLIST=$(srun hostname | sort | uniq -c | awk '{print $2 ":" $1}' | tr '\n' ':' | sed 's/:$/\n/g')
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mapdl -b -dis -mpi intelmpi -machines $HOSTLIST -np ${SLURM_NTASKS} -i "$SOLVER_FILE"
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else
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# IBMMPI (default) will be aware of the distribution of tasks.
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# - In principle, no need to force tasks distribution
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mapdl -b -dis -mpi ibmmpi -np ${SLURM_NTASKS} -i "$SOLVER_FILE"
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fi
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```
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In the above example, one can increase the number of *nodes* and/or *ntasks* if needed and combine it
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with `--exclusive` when necessary. In general, **no hypertheading** is recommended for MPI based jobs.
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Also, one can combine it with `--exclusive` when necessary.
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