AlphaFold Quickstart

Owned by RIS-SVC-conf-publish
Last updated: Jun 06, 2023
2 min read

Compute Resources

Docker Usage

Software Included

Getting Started

  • Connect to compute client.

ssh wustlkey@compute1-client-1.ris.wustl.edu

  • Prepare the computing environment before submitting an AlphaFold job.

  # Set the AlphaFold base directory
  export ALPHAFOLD_BASE_DIR=/app/alphafold

  # Use the scratch file system for temp space
  export SCRATCH1=/scratch1/fs1/${COMPUTE_ALLOCATION}

  # Use your Active storage for input and output data
  export STORAGE1=/storage1/fs1/${STORAGE_ALLOCATION}/Active

  # Mount scratch, Active storage, home directory and AlphaFold database reference files
  export LSF_DOCKER_VOLUMES="/scratch1/fs1/ris/references/alphafold_db:/scratch1/fs1/ris/references/alphafold_db $SCRATCH1:$SCRATCH1 $STORAGE1:$STORAGE1 $HOME:$HOME"

  # Update $PATH with folders containing AlphaFold, CUDA, and conda executables
  export PATH="/usr/local/cuda/bin/:/opt/conda/bin:/app/alphafold:$PATH"

  # Use the debug flag when trying to figure out why your job failed to launch on the cluster
  #export LSF_DOCKER_RUN_LOGLEVEL=DEBUG


- The following run example implements AlphaFold's suggested system requirements for database preset ``reduced_dbs``.
bsub -q general -n 8 -M 8GB -R "gpuhost rusage[mem=8GB] span[hosts=1]" -gpu 'num=1' -a "docker(gcr.io/ris-registry-shared/alphafold:2.2.0)" python3 /app/alphafold/run_alphafold.py --output_dir /path/to/output/folder --model_preset monomer --fasta_paths /path/to/input/protein_sequence.fa --max_template_date 2021-08-18 --db_preset reduced_dbs

  • AlphaFold can run by default on both V100 and A100 GPU architectures. Modify the -gpu argument to specify the GPU architecture.

-gpu 'num=1:gmodel=<gpu_model>'

  • A list of GPU models can be found here.

  • Jobs can be managed using job groups. Job groups are a way to submit a large number of jobs at once.

Additional Information

Please refer to official AlphaFold documentation for direction on setting up run options, expected output, example runs, etc.

Earlier Versions

Earlier versions are still available but no longer directly supported by RIS. Please refer to the latest version for direct support.