| # Running HADDOCK3 with MPI |
|
|
| To run this example you must have `mpi4py` installed in the haddock3 python |
| environment, and `OpenMPI` in the host system. |
|
|
| ```bash |
| $ pip install mpi4py |
| # or |
| $ conda install -c conda-forge mpi4py |
| ``` |
|
|
| **Do not run it as: `mpirun -np haddock3 run.cfg`**, this logic is handled |
| internally. |
|
|
| Edit the `.cfg` according to the `.job` parameters you have set |
|
|
| In the `.job` header: |
|
|
| ```bash |
| #SBATCH --nodes=5 |
| #SBATCH --tasks-per-node=96 |
| ``` |
|
|
| In the `.cfg` params |
|
|
| ```toml |
| ncores = 480 |
| ``` |
|
|
| Then prepare the rest of the `.job` file according to your cluster, a SLURM |
| example is provided at |
| `haddock3/examples/docking-protein-protein/docking-protein-protein-mpi.job` and |
| below: |
|
|
| ```bash |
| #!/bin/bash |
| #SBATCH --nodes=5 |
| #SBATCH --tasks-per-node=96 |
| #SBATCH -J haddock3mpi |
| |
| # make sure anaconda is activated |
| source $HOME/software/miniconda3/bin/activate |
| conda activate haddock3 |
| |
| # go to the example directory |
| cd $HOME/repos/haddock3/examples/docking-protein-protein |
| |
| # remove any old runs |
| rm -rf run-mpi |
| |
| # execute |
| haddock3 docking-protein-protein-mpi-test.cfg |
| ``` |
|
|
| Then: |
|
|
| ```bash |
| sbatch docking-protein-protein-mpi.job |
| ``` |
|
|
| Please report any errors as an [issue](https://github.com/haddocking/haddock3/issues/new/choose). |
|
|
