AlphaFold 3¶
We provide AlphaFold v3.0.3 on the HPC for use by approved users.
Note
AlphaFold 3 requires an NVIDIA GPU with a Compute Capability 8.0 or greater, which includes the Ampere, Ada Lovelace, Hopper, and Blackwell architectures.
Approval process¶
We restrict access to the AlphaFold 3 model parameters to users who have accepted their terms of service. To become an approved user, follow these steps:
- Complete this Google form.
- Within 3 business days, you should receive an email from alphafold@google.com that starts with "I'm writing to confirm that you have been granted access to the AlphaFold 3 model parameters subject to the AlphaFold 3 Model Parameters Terms of Use."
- Forward this email to divilovk@oregonstate.edu
- CQLS staff will manually add you to a user group with access to the model parameters and will respond to your email stating that you have been approved.
- Once approved, you can immediately run the command below to run AlphaFold 3. We provide an HPC-wide model parameters file so you don't need to use your personal file.
Using AlphaFold 3 on the HPC¶
We provide AlphaFold v3.0.3 on the HPC as singularity containers located in
/local/cqls/singularity/images/. Both x86 and ARM containers are provided.
The command to run the x86 container is:
singularity run --nv \
--bind /local/cqls/db \
/local/cqls/singularity/images/alphafold_v3.0.3_x86.sif \
--model_dir=/local/cqls/db/alphafold3_params \
--db_dir=/local/cqls/db/alphafold3 \
--json_path=input/fold_input.json \
--output_dir=output
This command assumes that in your working directory you have an input file
fold_input.json that is in the input folder and the output will be sent to
the output folder.
Adjust these variables to your preference. Change alphafold_v3.0.3_x86.sif
to alphafold_v3.0.3_arm.sif to run the ARM container.
To see the full or short help menus, run
singularity run --nv /local/cqls/singularity/images/alphafold_v3.0.3_x86.sif
with the --helpfull or --helpshort flags.