AlphaFold on Quest

How to run AlphaFold on Quest

For more details on AlphaFold 2, please visit the AlphaFold website.

How is AlphaFold Installed On Quest?

AlphaFold 2 is installed inside of a Singularity container following the instructions from the DeepMind team.

The container contains CUDA 11.0, Python 3.7.10, and TensorFlow 2.5.0.

Instead of calling singularity directly, we provide a module which wraps the call to the singularity run.

module load alphafold/2.0.0

This creates a shell function called alphafold which can be used as follows:

alphafold --fasta_paths=/full/path/to/fasta \
--output_dir=/full/path/to/outdir \
--model_names= \
--preset=[full_dbs|casp14] \
--max_template_date=

If you would like to see the contents of the shell function alphafold, you can run type alphafold on the command line.

How do you run AlphaFold on Quest?

Below, we provide an example submission script for running AlphaFold on Quest.

#!/bin/bash
#SBATCH --account=pXXXX  ## YOUR ACCOUNT pXXXX or bXXXX
#SBATCH --partition=gengpu  ### PARTITION (buyin, short, normal, etc)
#SBATCH --nodes=1 ## how many computers do you need - for AlphaFold this should always be one
#SBATCH --ntasks-per-node=12 ## how many cpus or processors do you need on each computer
#SBATCH --gres=gpu:a100:1  ## type of GPU requested, and number of GPU cards to run on
#SBATCH --time=48:00:00 ## how long does this need to run 
#SBATCH --mem=85G ## how much RAM do you need per node (this effects your FairShare score so be careful to not ask for more than you need))
#SBATCH --job-name=run_AlphaFold  ## When you run squeue -u <NETID> this is how you can identify the job
#SBATCH --output=AlphaFold.log ## standard out and standard error goes to this file
#SBATCH --mail-type=ALL ## you can receive e-mail alerts from SLURM when your job begins and when your job finishes (completed, failed, etc)
#SBATCH --mail-user=email@northwestern.edu ## your email, non-Northwestern email addresses may not be supported

#########################################################################
### PLEASE NOTE:                                                      ###
### The above CPU, Memory, and GPU resources have been selected based ###
### on the computing resources that alphafold was tested on           ###
### which can be found here:                                          ###
### https://github.com/deepmind/alphafold#running-alphafold)          ###
### It is likely that you do not have to change anything above        ###
### besides your allocation, and email (if you want to be emailed).   ###
#########################################################################

module purge 
module load alphafold/2.0.0

# template
# alphafold --fasta_paths=/full/path/to/fasta \
#    --output_dir=/full/path/to/outdir \
#    --model_names= \
#    --preset=[full_dbs|casp14] \
#    --max_template_date=

# real example
alphafold --output_dir $HOME/alphafold --fasta_paths=/projects/intro/alphafold/T1050.fasta --max_template_date=2021-07-28 --model_names model_1,model_2,model_3,model_4,model_5 --preset casp14

See Also:




Keywords:research computing, quest, alphafold, GPU   Doc ID:112835
Owner:Research Computing .Group:Northwestern
Created:2021-08-04 07:39 CDTUpdated:2021-08-06 16:13 CDT
Sites:Northwestern
CleanURL:https://kb.northwestern.edu/alphafold-on-quest
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