Table des matières
AMS on Jean Zay
Introduction
AMS is a molecular modeling software using the density functional theory.
Useful sites
Available versions
Attention: a bug was found in versions prior to 2020.103. It impacts analytical frequencies computation in some cases.
Version | Modules to load |
---|---|
2024.103 MPI | ams/2024.103-mpi |
2023.104 MPI | ams/2023.104-mpi |
2022.103 MPI | ams/2022.103-mpi |
2021.102 MPI | ams/2021.102-mpi |
2020.103 MPI | ams/2020.103-mpi |
2020.101 MPI | ams/2020.101-mpi |
2019.305 MPI | adf/2019.305-mpi |
2019.104 MPI CUDA | adf/2019.104-mpi-cuda cuda/10.1.1 |
Using the graphical interface AMSview
To use the graphical interface, it is necessary to use versions starting from 2024.103.
Information about GPU porting
All the ADF functions are not available on GPU. Please consult the dedicated page on the Web site if you wish to use this version.
Example of usage on the CPU partition
- adf.slurm
#!/bin/bash #SBATCH --nodes=1 # Number of nodes #SBATCH --ntasks-per-node=40 # Number of tasks per node #SBATCH --cpus-per-task=1 # Number of OpenMP threads per task #SBATCH --hint=nomultithread # Disable hyperthreading #SBATCH --job-name=ADF # Jobname #SBATCH --output=ADF.o%j # Output file #SBATCH --error=ADF.o%j # Error file #SBATCH --time=10:00:00 # Expected runtime HH:MM:SS (max 100h) ## ## Please, refer to comments below for ## more information about these 4 last options. ##SBATCH --account=<account>@cpu # To specify cpu accounting: <account> = echo $IDRPROJ ##SBATCH --partition=<partition> # To specify partition (see IDRIS web site for more info) ##SBATCH --qos=qos_cpu-dev # Uncomment for job requiring less than 2 hours ##SBATCH --qos=qos_cpu-t4 # Uncomment for job requiring more than 20h (up to 4 nodes) # Cleans out the modules loaded in interactive and inherited by default module purge # Load the necessary modules module load adf/2019.104-mpi-cuda export SCM_TMPDIR=$JOBSCRATCH # Execute command ./opt.inp
Usage example on the GPU partition
- adf.slurm
#!/bin/bash #SBATCH --nodes=1 # Number of nodes #SBATCH --gres=gpu:4 # Allocate 4 GPUs per node #SBATCH --ntasks-per-node=40 # Number of tasks per node #SBATCH --cpus-per-task=1 # Number of OpenMP threads per task #SBATCH --hint=nomultithread # Disable hyperthreading #SBATCH --job-name=ADF # Jobname #SBATCH --output=ADF.o%j # Output file #SBATCH --error=ADF.o%j # Error file #SBATCH --time=10:00:00 # Expected runtime HH:MM:SS (max 100h for V100, 20h for A100) ## ## Please, refer to comments below for ## more information about these 4 last options. ##SBATCH --account=<account>@v100 # To specify gpu accounting: <account> = echo $IDRPROJ ##SBATCH --partition=<partition> # To specify partition (see IDRIS web site for more info) ##SBATCH --qos=qos_gpu-dev # Uncomment for job requiring less than 2 hours ##SBATCH --qos=qos_gpu-t4 # Uncomment for job requiring more than 20h (up to 16 GPU, V100 only) # Manage modules module purge module load adf/2019.104-mpi-cuda cuda/10.1.1 # JOBSCRATCH is automatically deleted at the end of the job export SCM_TMPDIR=$JOBSCRATCH # Execution ./opt.inp
Comments:
- All jobs have resources defined in Slurm per partition and per QoS (Quality of Service) by default. You can modify the limits by specifying another partition and / or QoS as shown in our documentation detailing the partitions and Qos.
- For multi-project users and those having both CPU and GPU hours, it is necessary to specify the project accounting (hours allocation for the project) for which to count the job's computing hours as indicated in our documentation detailing the project hours management.