Nvidia’s AI-powered supercomputers advance nuclear fusion research

The most powerful supercomputers on the planet are used to perform all kinds of complex operations. Increasingly, they are being used to enable artificial intelligence for research that could one day impact billions of people.

The world’s fastest and most powerful high-performance computing (HPC) supercomputers are at the forefront of the International High Performance Computing (ISC) Conference taking place May 29-June 2 in Hamburg, Germany. As part of the ISC event, Nvidia will give an overview of its latest HPC systems and the use cases they enable.

“HPC plus AI is truly the transformative tool for scientific computing,” Dion Harris, senior technical product marketing manager for accelerated computing, said at a pre-ISC press conference. “We are talking about exascale AI because we believe it will be one of the main essential tools to drive scientific innovation and any data center building a supercomputer needs to understand how their system will perform from an AI perspective. .”

US-based Grace Hopper supercomputer arrives at Los Alamos National Laboratory

Nvidia first announced its Grace ARM-based processors in April 2021, aiming to include them in HPC deployments. The goal is happening now.

At ISC 2022, Nvidia announces that Los Alamos National Laboratory and Hewlett Packard Enterprise (HPE) are building Venado, which is the first US-based supercomputer to use the Grace chip architecture.

The Venado supercomputer uses a combination of Grace and Grace Hopper superchips, in a system that is expected to deliver 10 exaflops of AI performance. The Venado system will be used for materials science, renewable energy, as well as power distribution research.

Nvidia-powered AI enables brain imaging research

Brain imaging is among the HPC and AI use cases that Nvidia is announcing at ISC 2022.

King’s College London uses the Cambridge-1 system powered by Nvidia, which is the most powerful supercomputer in the UK, as well as the Monai AI open source framework optimized for medical imaging use cases.

Powerful hardware and AI software have been used to produce the world’s largest database of synthetic brain images.

The reason that matters is the amount of research focused on AI to identify conditions such as Alzheimer’s disease or dementia, Harris explained. “But to train these models, you need large databases,” he said.

There are many privacy issues when using real patient data, which is why it’s important that researchers have access to synthetic data, he added.

“It’s a true example of HPC not just delivering speeds and flows, but actually making real contributions to the science and research community,” Harris said.

Modeling of a nuclear fusion reactor

As people around the world try to find solutions to the challenges of global warming, one of the main strategies is to identify renewable energy sources.

One such source could be nuclear fusion reactors. Today’s nuclear reactors are based on fission and generate radioactive waste. The promise of fusion is that it can deliver vast amounts of energy, without the same waste products as fission.

At ISC 2022, Nvidia announces that the UK Atomic Energy Authority (AEA) is using the Nvidia Omniverse simulation platform to accelerate the design and development of a full-scale fusion reactor.

“With the Nvidia Omniverse, researchers could potentially build a fully functional digital twin of a reactor, helping to ensure that the most efficient designs are selected for construction,” Harris said.

The goal of Omniverse and the digital twin is to have an AI-generated replica of the fusion reactor system. The UK AEA also plans to simulate the physics of the Fusion plasma confinement itself. The simulation will be performed with the Nvidia Modulus AI-physics framework to actually model how the fusion reaction and its confinement can occur.

“The holy grail of fusion power is being able to not only create a fusion reaction, but also make it sustainable,” Harris said. “We really think this will be a path to sustainable energy.”

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