Less than five months ago, the novel coronavirus (formally known as SARS-CoV-2) was unknown. By 1st May, at the time of writing, Covid-19 – the disease caused by the novel coronavirus – has claimed the lives of almost a quarter of a million people, and has changed the lives of billions as it has spread to almost every country in the world. In the same period, the global scientific community have learned an extraordinary amount about the virus, how it is spreading, and how we might combat it.

The extent of our knowledge, and the phenomenal speed with which it has been acquired, would not be possible without high-performance computing (HPC). Given the colossal global numbers to analyse – 3.4m cases, 2m active patients, 1.3m cases with an outcome, 10m Covid-19 tests, across 212 countries with 4.5b people living with social distancing – and the majority of these numbers changing minute-by-minute, there has never been a moment in time when the world needed HPC more.

HPC gives us the potential to analyse vast data sets – including almost 30,000 documents made available by the White House in March alone – to plot the path of outbreaks and pandemics like Covid-19, predict the evolution and to simulate vaccine compounds – all at remarkable speed.

Clearly, it’s sometimes hard for a non-scientific ‘lay person’ like myself to quantify ‘remarkable speed’ when it comes to scientific discovery, so to provide some form of comparison, after HIV-1, the main cause of AIDS in humans was first identified in 1981, it took almost three decades to genetically decode HIV-1. Four years later, in 2013, the SARS outbreak (due to another coronavirus) was decoded within three months. The genome behind Covid-19 was decoded and published globally within days. The speed at which science, scientists and their supercomputers are now working at is truly staggering, especially when you remember they’re not all focused on the same part of the puzzle at the same time.

Faced with a newly discovered and rapidly spreading virus, there are a myriad of steps that scientists and healthcare workers need to take. First, they have to be able to diagnose new cases. Then, they need to predict how and where it is spreading. Next comes the search for treatment options, which means understanding how the virus works and testing drug candidates. HPC is playing a vital role at each and every stage.

Spotting a pandemic

The initial challenge for clinicians and researchers in China was correctly diagnosing which patients had the disease, at a time when test kits were limited and not always reliable. Tianhe-1, China’s first petascale computer, housed at the National Supercomputing Centre in Tianjin, was used to distinguish between CT scans of patients with Covid-19 pneumonia and non-Covid-19 pneumonia. With the former being highly contagious, the distinction was vitally important. Researchers reported almost 80 per cent accuracy – better than both early test kits and human radiologists.

As the virus took hold, remarkably it was artificial intelligence running on HPC platforms that was first to identify the spread. BlueDot, a company based in Toronto, Canada, that tracks infectious diseases, warned of a problem in late December – a full week before America’s Centre for Disease Control and the World Health Organization.

Crucial to the spread of Covid-19 is that patients are infectious for several days before developing symptoms. BlueDot uses official and unofficial sources, including global airline ticketing data, to predict where infected people might be travelling. This has helped health authorities plan their resources and has given governments a sense of where lockdown measures and social isolation might be necessary.

Breaking down the virus

Seven weeks after the first case of Covid-19 in the United States on 21st January, the White House set up the COVID-19 High Performance Computing Consortium. This brought together federal government, industry and academic leaders to provide access to 16 of the world’s most powerful HPC resources. Combined, these armed the fight against Covid-19 with 424 petaflops, 3,800,000 CPU cores, and 41,000 GPUs (graphics processing units). All accessible and focused on one aim – to bring an end to the Covid-19 pandemic, and quickly.

Collectively that’s the computing power of almost 500,000 laptops – the scientific computing equivalent of absolute brute force – a digital, heavy-iron bulldozer smashing its way through mountains and mountains of big data.

Another issue is making sure the data to be analysed is as much as possible in the same place. In Europe, the Covid-19 Data Portal was set-up by EMBL-EBI and partners in April to bring together relevant datasets for sharing and analysis in an effort to accelerate coronavirus research. It enables researchers to upload, access and analyse Covid-19 related reference data and specialist datasets as part of the wider European Covid-19 Data Platform.

NVIDIA has also been providing researchers with free access to Parabricks, its gene sequencing tool, which can accelerate data analysis by up to 50 times. Meanwhile, Intel has partnered with Lenovo and BGI Genomics to investigate Covid-19 transmission patterns. Following the mutations of the virus is fundamental to finding a vaccine or treatments.

Understandably, focus on a vaccine is intense, and assessing drug candidates is one area in which HPC particularly excels. In Europe, CINECA, one of the top 20 most powerful supercomputers in the world, is part of a consortium of researchers – including the Barcelona Supercomputing Center and the Julich Supercomputing Centre – that are working on a vaccine, using code and workflows developed to research the Zika virus.

In the US, Summit, the world’s most powerful supercomputer based at Oak Ridge National Labs, has been simulating 8,000 possible vaccine compounds. It found 77 candidates in just a few days – something that would have taken years by hand and months on a ‘normal’ computer.

Much remains uncertain as the world tries to cope with the pandemic, however what is certain is that high performance computing is giving us the analysis, statistics and insights to make better, more informed, quicker decisions that will, ultimately, save thousands of lives.

And finally, it’s worth remembering that HPC doesn’t run itself. The army of mission-critical technicians, engineers and support staff who are quietly behind the scenes keeping the lights flashing and the servers whirling in data centres, laboratories and research institutes around the world, deserve our considerable thanks and appreciation.