AlphaFold
- Elyn Fritz-Waters
Compute Resources
Have questions or need help with compute, including activation or issues? Follow this link.
Docker Usage
The information contained on this page assumes that you have a knowledge base of using Docker to create images and push them to a repository for use. If you need to review that information, please see the links below.
Docker Basics: Building, Tagging, & Pushing A Custom Docker Image
storageN
The use of
storageNwithin these documents indicates that any storage platform can be used.Current available storage platforms:
storage1
storage2
Software Included
AlphaFold v2.2.0 (GitHub - google-deepmind/alphafold: Open source code for AlphaFold 2. )
Getting Started
Connect to compute client.
ssh wustlkey@compute1-client-1.ris.wustl.eduPrepare 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/${COMPUTE_ALLOCATION}
# Use your Active storage for input and output data
export STORAGE1=/storageN/fs1/${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_dbsAlphaFold can run by default on both V100 and A100 GPU architectures. Modify the
-gpuargument 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.