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| author | galaxy-australia |
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| date | Sun, 28 Jul 2024 20:09:55 +0000 |
| parents | f9eb041c518c |
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Alphafold compute setup ======================= Overview -------- Alphafold requires a customised compute environment to run. The machine needs a GPU, and access to a 2.2 Tb reference data store. This document is designed to provide details on the compute environment required for Alphafold operation, and the Galaxy job destination settings to run the wrapper. We strongly suggest reading this entire document to ensure that your setup is compatible with the hardware that you are deploying to. For full details on Alphafold requirements, see https://github.com/deepmind/alphafold. HARDWARE ~~~~~~~~ The machine is recommended to have the following specs: - 12 cores - 80 Gb RAM - 2.5 Tb storage - A fast Nvidia GPU. As a minimum, the Nvidia GPU must have 8Gb RAM. It also requires **unified memory** to be switched on. Unified memory is usually enabled by default, but some HPC systems will turn it off so the GPU can be shared between multiple jobs concurrently. ENVIRONMENT ~~~~~~~~~~~ This wrapper runs Alphafold as a singularity container. The following software are needed: - `Singularity <https://sylabs.io/guides/3.0/user-guide/installation.html>`_ - `NVIDIA Container Toolkit <https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html>`_ As Alphafold uses an Nvidia GPU, the NVIDIA Container Toolkit is needed. This makes the GPU available inside the running singularity container. To check that everything has been set up correctly, run the following :: singularity run --nv docker://nvidia/cuda:11.0-base nvidia-smi If you can see something similar to this output (details depend on your GPU), it has been set up correctly. :: +-----------------------------------------------------------------------------+ | NVIDIA-SMI 470.57.02 Driver Version: 470.57.02 CUDA Version: 11.4 | |-------------------------------+----------------------+----------------------+ | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 Tesla T4 Off | 00000000:00:05.0 Off | 0 | | N/A 49C P0 28W / 70W | 0MiB / 15109MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+ REFERENCE DATA ~~~~~~~~~~~~~~ Alphafold needs reference data to run. The wrapper expects this data to be present at ``/$ALPHAFOLD_DB/TOOL_MINOR_VERSION``. Where ``ALPHAFOLD_DB`` is a custom path that will be read from the ``ALPHAFOLD_DB`` environment variable (defaulting to ``/data``). And TOOL_MINOR_VERSION is the alphafold version, e.g. ``2.3.1``. To download the AlphaFold reference DBs: :: # Set your AlphaFold DB path ALPHAFOLD_DB=/data/alphafold_databases/2.3.1 # Set your target AlphaFold version ALPHAFOLD_VERSION=2.3.1 # Download repo wget https://github.com/deepmind/alphafold/releases/tag/v${ALPHAFOLD_VERSION}.tar.gz tar xzf v${ALPHAFOLD_VERSION}.tar.gz # Ensure dirs mkdir -p $ALPHAFOLD_DB # Download bash alphafold*/scripts/download_all_data.sh $ALPHAFOLD_DB You will most likely want to run this as a background job, as it will take a very long time (7+ days in Australia). This will install the reference data to your ``$ALPHAFOLD_DB``. To check this has worked, ensure the final folder structure is as follows: :: # NOTE: this structure will change between minor AlphaFold versions # The tree shown below was updated for v2.3.1 data/alphafold_databases/2.3.1/ ├── bfd │ ├── bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt_a3m.ffdata │ ├── bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt_a3m.ffindex │ ├── bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt_cs219.ffdata │ ├── bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt_cs219.ffindex │ ├── bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt_hhm.ffdata │ └── bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt_hhm.ffindex ├── mgnify │ └── mgy_clusters_2022_05.fa ├── params │ ├── LICENSE │ ├── params_model_1.npz │ ├── params_model_1_multimer_v3.npz │ ├── params_model_1_ptm.npz │ ├── params_model_2.npz │ ├── params_model_2_multimer_v3.npz │ ├── params_model_2_ptm.npz │ ├── params_model_3.npz │ ├── params_model_3_multimer_v3.npz │ ├── params_model_3_ptm.npz │ ├── params_model_4.npz │ ├── params_model_4_multimer_v3.npz │ ├── params_model_4_ptm.npz │ ├── params_model_5.npz │ ├── params_model_5_multimer_v3.npz │ └── params_model_5_ptm.npz ├── pdb70 │ ├── md5sum │ ├── pdb70_a3m.ffdata │ ├── pdb70_a3m.ffindex │ ├── pdb70_clu.tsv │ ├── pdb70_cs219.ffdata │ ├── pdb70_cs219.ffindex │ ├── pdb70_hhm.ffdata │ ├── pdb70_hhm.ffindex │ └── pdb_filter.dat ├── pdb_mmcif │ ├── mmcif_files │ └── obsolete.dat ├── pdb_seqres │ └── pdb_seqres.txt ├── uniprot │ └── uniprot.fasta ├── uniref30 │ ├── UniRef30_2021_03.md5sums │ ├── UniRef30_2021_03_a3m.ffdata │ ├── UniRef30_2021_03_a3m.ffindex │ ├── UniRef30_2021_03_cs219.ffdata │ ├── UniRef30_2021_03_cs219.ffindex │ ├── UniRef30_2021_03_hhm.ffdata │ └── UniRef30_2021_03_hhm.ffindex └── uniref90 └── uniref90.fasta In more recent releases of the AlphaFold tool, you will need to download an additional file to allow the ``reduced_dbs`` option: :: bash scripts/download_small_bfd.sh $ALPHAFOLD_DB_ROOT The ``$ALPHAFOLD_DB_ROOT`` directory should now contain this additional file: :: data/alphafold_databases/2.3.1/ ├── small_bfd │ └── bfd-first_non_consensus_sequences.fasta **Upgrading database versions** When upgrading to a new minor version of AlphaFold, you will most likely have to upgrade the reference database. This can be a pain, due to the size of the databases and the obscurity around what has changed. The simplest way to do this is simply create a new directory and download the DBs from scratch. However, you can save a considerable amount of time by downloading only the components that have changed. If you wish to continue hosting prior versions of the tool, you must maintain the reference DBs for each version. The ``ALPHAFOLD_DB`` environment variable must then be set respectively for each tool version in your job conf (on Galaxy AU this is currently `configured with TPV <https://github.com/usegalaxy-au/infrastructure/blob/master/files/galaxy/dynamic_job_rules/production/total_perspective_vortex/tools.yml#L1515-L1554>`_). To minimize redundancy between DB version, we have symlinked the database components that are unchanging between versions. In ``v2.1.2 -> v2.3.1`` the BFD database is the only component that is persistent, but they are by far the largest on disk. JOB DESTINATION ~~~~~~~~~~~~~~~ Alphafold needs a custom singularity job destination to run. The destination needs to be configured for singularity, and some extra singularity params need to be set as seen below. Specify the job runner. For example, a local runner :: <plugin id="alphafold_runner" type="runner" load="galaxy.jobs.runners.local:LocalJobRunner"/> Customise the job destination with required singularity settings. The settings below are mandatory, but you may include other settings as needed. :: <destination id="alphafold" runner="alphafold_runner"> <param id="dependency_resolution">'none'</param> <param id="singularity_enabled">true</param> <param id="singularity_run_extra_arguments">--nv</param> <param id="singularity_volumes">"$job_directory:ro,$tool_directory:ro,$job_directory/outputs:rw,$working_directory:rw,/data/alphafold_databases:/data:ro"</param> </destination> CUSTOM PARAMETERS ~~~~~~~~~~~~~~~~~ A few parameters can be customized with the use of environment variables set in the job destination: - ``ALPHAFOLD_DB``: path to the reference database root (default ``/data``) - ``ALPHAFOLD_USE_GPU [True/False]``: set to ``False`` to disable GPU dependency (defaults to ``True``) - ``ALPHAFOLD_AA_LENGTH_MIN``: minimum accepted sequence length (default ``0``) - ``ALPHAFOLD_AA_LENGTH_MAX``: maximum accepted sequence length (default ``0`` - no validation) Closing ~~~~~~~ If you are experiencing technical issues, feel free to write to help@genome.edu.au. We may be able to provide advice on setting up Alphafold on your compute environment.