We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.

Advertisement

Fighting COVID-19 With the Help of High-performance Computing

Fighting COVID-19 With the Help of High-performance Computing content piece image
Credit: Pixabay
Listen with
Speechify
0:00
Register for free to listen to this article
Thank you. Listen to this article using the player above.

Want to listen to this article for FREE?

Complete the form below to unlock access to ALL audio articles.

Read time: Less than a minute

High-performance computing (HPC) is one of the most powerful tools we have in the fight against disease, giving us detailed insight into the building blocks of viruses. OCF is assisting its customers to get involved in “Folding@home” in the fight against COVID-19.

Folding@home is a distributed computing project for simulating protein dynamics, including the process of protein folding and the movements of proteins implicated in a variety of diseases. It brings together scientists who volunteer to run simulations of protein dynamics on their personal computers and provide new opportunities for developing therapeutics.

This is an opportunity for any existing OCF customers and anyone with an x86 Slurm cluster to get involved in combatting COVID-19. OCF is helping universities and research institutions to donate any spare capacity in their existing solutions to the COVID-19 sequencing effort through Folding@home. Spare capacity can be utilized when users are not using all HPC resources and any donation of clock cycles doesn’t need to impact on any current workloads you are working on. GPU capacity is the most sought after at this time, but all donated resources help.

Organizations already joining the Folding@home effort include the University of Aberdeen, the University of East Anglia and Plymouth Marine Laboratory.

To help interested customers and any other organizations with HPC or GPU capabilities, OCF has shared a set of instructions for setting up Slurm scheduler in order to join the Folding@Home project, as well as resources on running in a containerized Kubernetes environment.