Jülich leverages QODA as a gateway to quantum computing

Kristel Michielsen was into quantum computing before quantum computing was cool.

The computational physicist simulated quantum computers as part of her PhD. work in the Netherlands in the early 1990s.

Today, she manages one of the largest quantum computing facilities in Europe, the Jülich Unified Infrastructure for Quantum Computing (JUNIQ). Its mission is to help developers open up this new realm with tools like NVIDIA Quantum Optimized Device Architecture (QODA).

“It helps bring quantum computing closer to the HPC and AI communities.” -Kristel Michielsen

“We cannot continue with today’s classical computers alone because they consume so much energy and they cannot solve certain problems,” said Michielsen, who leads the quantum program at the Jülich Supercomputing Center near Cologne. “But paired with quantum computers that won’t consume as much power, I think there could be the potential to solve some of our most complex problems.”

Enter the QPU

Because quantum processors, or QPUs, exploit the properties of quantum mechanics, they are ideally suited for simulating processes at the atomic level. This could enable fundamental advances in chemistry and materials science, triggering domino effects in everything from more efficient batteries to more effective drugs.

QPUs can also help solve tricky optimization problems in areas like logistics. For example, airlines face daily challenges determining which aircraft to assign to which routes.

In one experiment, a quantum computer recently installed in Jülich showed the most efficient way to route nearly 500 flights, demonstrating the technology’s potential.

Quantum computing also promises to take AI to the next level. In separate experiments, the Jülich researchers used quantum machine learning to simulate how proteins bind to DNA strands and classify satellite images of Lyon, France.

Hybrids get the best of both worlds

Several quantum computer prototypes are now available, but none are yet powerful or reliable enough to tackle commercially relevant tasks. But researchers see a way forward.

“For a long time, we’ve had a vision of hybrid systems as the only way to achieve practical quantum computing — tied to today’s classical HPC systems, quantum computers will give us the best of both worlds,” Michielsen said. .

And that is exactly what Jülich and other researchers around the world are building today.

Quantum gets a 49x boost on A100 GPUs

In addition to its current analog quantum system, Jülich plans to install a neutral atom quantum computer from Paris-based Pasqal next year. He has also run quantum simulations on classical systems such as his JUWELS Booster, which contains more than 3,700 NVIDIA A100 Tensor Core GPUs.

“The GPU version of our Universal Quantum Computer Simulator, called JUQCS, has allowed us to speed up jobs running on CPU clusters by up to 49 times. This job uses almost every GPU node in the system and relies heavily on its InfiniBand network,” she said. , citing a recent article.

Recently, classic systems like the JUWELS Booster use NVIDIA cuQuantum, a software development kit to accelerate quantum tasks on GPUs. “For us it’s great for cross-platform benchmarking, and for others it could be a great tool to start or optimize their quantum simulation codes,” Michielsen said of the SDK.

The A100 GPUs (green) form the core of the JUWELS Booster which can simulate quantum tasks with the NVIDIA cuQuantum SDK.

Hybrid systems, hybrid software

With several HPC and quantum systems available and more on the way to Jülich and other research centers, one of the challenges is to tie everything together.

“The HPC community needs to dig deep into applications that span everything from climate science and medicine to chemistry and physics to see which parts of the code can work on quantum systems,” she said. declared.

It’s a Herculean task for developers entering the era of quantum computing, but help is on the way.

NVIDIA QODA acts as a software bridge. With a function call, developers can choose to run their quantum tasks on GPUs or quantum processors.

QODA’s high-level language will support all types of quantum computers and its compiler will be available as open source software. And it’s supported by quantum system and software vendors including Pasqal, Xanadu, QC Ware, and Zapata.

Quantum leap for HPC and AI developers

Michielsen expects JUNIQ to provide QODA to researchers across Europe who use its quantum services.

“It helps bring quantum computing closer to the HPC and AI communities,” she said. “It will speed up the way they get things done without them needing to do all the low-level programming, which will make their lives a whole lot easier.”

Michielsen expects many researchers to use QODA to test classical quantum hybrid computers – over the next year and beyond.

“Who knows, maybe one of our users will pioneer a new example of hybrid computing in the real world,” she said.

Visit the NVIDIA QODA site to learn more and apply for early interest. And get technical details about QODA here.

Top image courtesy of Forschungszentrum Jülich / Ralf-Uwe Limbach

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