Computational science relies on advanced computing and data analysis to solve complex scientific problems. Research-intensive institutions are always looking for ways to improve research methods to champion ground-breaking research and in turn attract new researchers, research funding, and expand on existing programmes of research and teaching.
High-Performance Computing (HPC), also known to some as supercomputing, is the infrastructure that unlocks this potential, helping to solve the most difficult of problems at a quicker rate.
From analysing complex genomics datasets to revolutionise the study of Earth’s biodiversity; to using deep learning for the early detection of respiratory disease; to identifying genetic mutation in genomes arising in cancerous cells, HPC is helping institutions all over the world with the significant memory and fast processing they desperately need for bulky, complex numerical computation.
Workloads are driving an ever-growing set of data-intensive challenges that can only be met with accelerated infrastructure. Previously, what would take researchers sometimes months, even years to process using a single desktop computer, can be run on HPC systems as high-volume simulations, generating outcomes in a significantly reduced timeframe, saving valuable time, scientific focus and cost.
“HPC could be the answer to help to discover new treatments. In fact, it is one of the most powerful tools we must help in the fight against COVID-19, giving us detailed insight into the building blocks of viruses.”
Today more than ever, the vital importance of HPC is clear and the opportunities that it provides. In the fight against the pandemic, scientists are currently simulating protein dynamics, including the process of protein folding and the movements of proteins implicated in a variety of diseases to provide new opportunities for developing therapeutics.
HPC could be the answer to help discovering new treatments. In fact, it is one of the most powerful tools we must help in the fight against COVID-19, giving us detailed insight into the building blocks of viruses.
Ordinarily, supercomputers are used to tackle the grand challenges of science and engineering on their own rather than as part of a distributed project. However, currently, universities and research institutions across the world are joining together to run huge simulations by donating spare capacity in their HPC solutions to provide new opportunities for the COVID-19 sequencing effort.
Spare GPU capacity within the HPC system can be utilised when users are not using all HPC resources, and any donation of clock cycles does not need to impact on any current workloads they are working on. This demonstrates the clear potential, showing how HPC can be utilised for the greater good.
Going forward, to enable scientists to work better towards cutting-edge innovation in computing, it will be important to develop and enhance the accessibility of HPC services to be less inhibitive and challenging to adopt. Likewise, the ability to transfer workloads or bespoke applications between HPC services by utilising containerisation will allow for greater flexibility, a collaboration between scientific communities and quicker turnaround in scientific research.
Data-driven initiatives are also driving developments within HPC through artificial intelligence (AI) and deep learning toolsets. These provide the ability to delve into vast volumes of data and produce actionable insights into that data. Scientific data is being generated at an ever-increasing rate, very often in largely unstructured formats, and making sense of that data is key to unlocking fresh insights in the world we live in.
It is these initiatives and use-cases that clearly demonstrate HPC has the ability to equip any institution with the potential to pioneer ground-breaking research and change the world for the better.