Installation of VFVS
Setting up AWS Batch
VFVS 2.0 on AWS uses an AWS Batch cluster and workload manager. Instructions on how to create the AWS Batch cluster, and how to access the AWS Batch login node can be found here on the VFVS GitHub page.
Setting up SSH
To log in to the AWS Batch login node via ssh, follow the instructions here. You will land in the home directory of the AWS Batch login node.
Setting up Python
VFVS requires Python 3.x (it has been tested with Python 3.9.4). Additionally, it requires packages to be installed that are not included at many sites. As a result, we recommend that you create a virtualenv for VFVS that can be used to run jobs.
Make sure that virtualenv is installed:
Create a virtualenv (this example creates it under $HOME/vfvs_env):
Enter the virtualenv and install needed packages
Alternatively, all the above steps can be performed using conda instead of pip. Further information on setting up a conda style environment can be found here.
To exit a virtual environment:
When running VFVS commands, you should enter the virtualenv that you have set up using:
Alternatively, all the above steps can be performed using conda instead of pip. Further information on setting up a conda style environment can be found here.
For the remainder of the tutorial and for future use of VFVS, please ensure the virtual environment is activated.
Installing VFVS 2.0
After Python is set up, we can install VFVS 2.0. Normally this is done by cloning the GitHub repo, but for this tutorial, we provide a pre-configured folder for download. On the AWS Batch login node, you can download it by running the following command:
This preconfigured folder was prepared by:
Cloning the GitHub repo (branch vfvs-2)
Adding the docking input files to the
input-filesfolderConfiguring the
all.ctrlfile. The following parameters are changed compared to the template file in the VFVS GitHub repo:job_namedocking_scenario_namesdocking_scenario_programsdocking_scenario_replicasdocking_scenario_batchsizes
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