Dedalus

Dedalus is a flexible framework for solving partial differential equations using modern spectral methods.

Available versions

Dedalus is available on our clusters as prebuilt Python packages (wheels). You can list available versions with avail_wheels.

[name@server ~]$ avail_wheels dedalus --all-versions
$ avail_wheels dedalus
name     version    python    arch
-------  ---------  --------  ---------
dedalus  3.0.2      cp311     x86-64-v3
dedalus  3.0.2      cp310     x86-64-v3

Installing Dedalus in a Python virtual environment

1. Load Dedalus runtime dependencies.

[name@server ~]$ module load StdEnv/2023 gcc openmpi mpi4py/3.1.4 fftw-mpi/3.3.10 hdf5-mpi/1.14.2 python/3.11

2. Create and activate a Python virtual environment.

[name@server ~]$ virtualenv --no-download ~/dedalus_env
[name@server ~]$ source ~/dedalus_env/bin/activate

3. Install a specific version of Dedalus and its Python dependencies.

(dedalus_env) [name@server ~] pip install --no-index --upgrade pip
(dedalus_env) [name@server ~] pip install --no-index dedalus==X.Y.Z

where X.Y.Z is the exact desired version, for instance 3.0.2. You can omit to specify the version in order to install the latest one available from the wheelhouse.

4. Validate it.

(dedalus_env) [name@server ~] python -c 'import dedalus'

5. Freeze the environment and requirements set.

(dedalus_env) [name@server ~] pip freeze --local > ~/dedalus-3.0.2-requirements.txt

6. Remove the local virtual environment.

(dedalus_env) [name@server ~] deactivate && rm -r ~/dedalus_env

Running Dedalus

You can run dedalus distributed accross multiple nodes or cores. For efficient MPI scheduling, please see:

• Running_jobs#MPI_job
• Advanced_MPI_scheduling

1. Write your job submission script.

DistributedWhole nodes

File : submit-dedalus-distributed.sh

#!/bin/bash

#SBATCH --account=def-someprof    # adjust this to match the accounting group you are using to submit jobs
#SBATCH --time=08:00:00           # adjust this to match the walltime of your job
#SBATCH --ntasks=4                # adjust this to match the number of tasks/processes to run
#SBATCH --mem-per-cpu=4G          # adjust this according to the memory you need per process

# Run on cores accross the system : https://docs.alliancecan.ca/wiki/Advanced_MPI_scheduling#Few_cores,_any_number_of_nodes

# Load modules dependencies.
module load StdEnv/2023 gcc openmpi mpi4py/3.1.4 fftw-mpi/3.3.10 hdf5-mpi/1.14.2 python/3.11

# create the virtual environment on each allocated node: 
srun --ntasks $SLURM_NNODES --tasks-per-node=1 bash << EOF
virtualenv --no-download $SLURM_TMPDIR/env
source $SLURM_TMPDIR/env/bin/activate

pip install --no-index --upgrade pip
pip install --no-index -r dedalus-3.0.2-requirements.txt
EOF

# activate only on main node
source $SLURM_TMPDIR/env/bin/activate;

export OMP_NUM_THREADS=1

# srun exports the current env, which contains $VIRTUAL_ENV and $PATH variables
srun python $SCRATCH/myscript.py;

File : submit-dedalus-whole-nodes.sh

#!/bin/bash

#SBATCH --account=def-someprof    # adjust this to match the accounting group you are using to submit jobs
#SBATCH --time=08:00:00           # adjust this to match the walltime of your job
#SBATCH --nodes=2                 # adjust this to match the number of whole node
#SBATCH --ntasks-per-node=4       # adjust this to match the number of tasks/processes to run per node
#SBATCH --mem-per-cpu=4G          # adjust this according to the memory you need per process

# Run on N whole nodes : https://docs.alliancecan.ca/wiki/Advanced_MPI_scheduling#Whole_nodes

# Load modules dependencies.
module load StdEnv/2023 gcc openmpi mpi4py/3.1.4 fftw-mpi/3.3.10 hdf5-mpi/1.14.2 python/3.11

# create the virtual environment on each allocated node: 
srun --ntasks $SLURM_NNODES --tasks-per-node=1 bash << EOF
virtualenv --no-download $SLURM_TMPDIR/env
source $SLURM_TMPDIR/env/bin/activate

pip install --no-index --upgrade pip
pip install --no-index -r dedalus-3.0.2-requirements.txt
EOF

# activate only on main node
source $SLURM_TMPDIR/env/bin/activate;

export OMP_NUM_THREADS=1

# srun exports the current env, which contains $VIRTUAL_ENV and $PATH variables
srun python $SCRATCH/myscript.py;

2. Submit your job to the scheduler.

Before submitting your job, it is important to test that your submission script will start without errors. You can do a quick test in an interactive job.

[name@server ~]$ sbatch submit-dedalus.sh

Message Passing Interface