COVID-19 News

From animation to medicinal plants, COVID-19 HPC Consortium broadens scope

A supercomputer rendering of airflow in an empty hospital room, where the vertical velocity of air is high enough to keep the virus-laden aerosols in suspension. The colors represent velocity of the ambient air (highest is blue, lowest is red). (Source: Utah State University/IBM)

On March 17th, Dario Gil, the director of IBM Research, called Michael Kratsios, the US government’s chief technology officer, and proposed the creation of a consortium of supercomputers that could accelerate research projects addressing the rapidly spiraling Covid-19 pandemic.

Five days later, dozens of partners had joined the Consortium, including the US National Laboratories, National Science Foundation, NASA, various universities, Microsoft, Google, Amazon, Hewlett Packard Enterprise, and many more.

It took one kick-off phone call and less than a week for Gil and Kratsios to form the largest public-private computing partnership ever created — and they did it without generating sheaves of contracts. Several European supercomputers have just joined the fight.These institutions and companies recognized the need to act immediately to commit resources and match them to relevant research proposals.

The Covid-19 HPC Consortium has been up and running for more than two months and in that time, 56 Covid-19-related research projects have been granted free supercomputer resources. The Consortium has so far donated 430 Petaflops from more than 40 partners.

Modeling the spread

One project benefiting from the consortium’s computing power is mapping how Covid-19-containing droplets move through the air. This project, undertaken by researchers from Utah State University in collaboration with the Lawrence Livermore National Lab and the University of Illinois, simulates air turbulence to examine how the virus spreads. This is a critical area of research as the virus’ transmission pathways in hospitals and indoor areas are not fully understood.

Complex multi-phase turbulence simulations of virus-laden droplet clouds are calculated by the supercomputer to understand how the particles move and where they settle. There’s an example below. This animation represents the air coming into a 14-ft hospital room through the air conditioning system (the team is also running simulations on bigger rooms).

Utah State University Professor Som Dutta, who is a researcher on the project, explained to EE Times that the inflow and outflow of the air in a hospital room is one of the main drivers of aerosol transport, especially for asymptomatic carriers, who often don’t sneeze or cough but generate aerosols just by talking or breathing. Dutta explained that for very small aerosol droplets (smaller than 5µm), such as those generated by talking, the droplets’ velocity will be similar to the velocity of the ambient air, whose velocity is dictated by the air conditioning.

This project aims to indicate regions of the room that might have droplets of a certain size in the air. The ultimate goal is to help develop non-pharmacological methods to reduce the spread of the virus.

Novel projects

Some of the other novel projects that have benefited from the consortium’s computing power include a project to look for anti-viral phytochemicals from India’s 3,000 medicinal indigenous plants. Indian company Novel Techsciences will use supercomputer time donated by the Consortium to identify phytochemicals that will work against Covid-19 protein targets. The company will also look for plant-derived compounds to tackle multi-drug resistance that may arise as Covid-19 evolves.

Atomic force fields are another area of research benefiting from the Consortium’s compute power. The potential energy generated by atoms can give an overall molecule a so-called force field, which can attract or repel other molecules. Researchers from the University of Utah, Thomas Cheatham and Rodrigo Galindo, had developed a workflow for molecular simulation of this phenomenon during the Ebola outbreak in 2014. Simulation software developed by Cheatham, running on the Longhorn supercomputer at the Texas Advanced Computing Center, has generated molecular models of more than 2,000 relevant compounds which have been ranked based on estimates of their force fields. The aim is to aid in selecting peptide inhibitors for Covid-19.

Meanwhile, NASA is trying to predict the spread of the virus by examining genetic traits that can make a person more susceptible to Covid-19 acute respiratory distress. This project involves genome sequencing and DNA sequencing carried out by supercomputers. The aim is to identify patients who are suited to clinical trials of vaccines and antivirals.

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