NVIDIA Accelerates Quantum Computing Centers Worldwide With CUDA-Q Platform

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Supercomputers in Germany, Japan and Poland Incorporate Grace-Hopper and Quantum-Classical Accelerated Supercomputing Platform to Advance Quantum Computing Research

NVIDIA quantum computing

NVIDIA accelerates quantum computing centers with the NVIDIA CUDA-Q platform.
NVIDIA accelerates quantum computing centers with the NVIDIA CUDA-Q platform.

HAMBURG, Germany, May 12, 2024 (GLOBE NEWSWIRE) — ISC — NVIDIA today announced that it will accelerate quantum computing efforts at national supercomputing centers around the world with the open-source NVIDIA CUDA-Q™ platform.

Supercomputing sites in Germany, Japan and Poland will use the platform to power the quantum processing units (QPUs) inside their NVIDIA-accelerated high-performance computing systems.

QPUs are the brains of quantum computers that use the behavior of particles like electrons or photons to calculate differently than traditional processors, with the potential to make certain types of calculations faster.

Germany’s Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich is installing a QPU built by IQM Quantum Computers as a complement to its JUPITER supercomputer, supercharged by the NVIDIA GH200 Grace Hopper™ Superchip.

The ABCI-Q supercomputer, located at the National Institute of Advanced Industrial Science and Technology (AIST) in Japan, is designed to advance the nation’s quantum computing initiative. Powered by the NVIDIA Hopper™ architecture, the system will add a QPU from QuEra.

Poland’s Poznan Supercomputing and Networking Center (PSNC) has recently installed two photonic QPUs, built by ORCA Computing, connected to a new supercomputer partition accelerated by NVIDIA Hopper.

“Useful quantum computing will be enabled by the tight integration of quantum with GPU supercomputing,” said Tim Costa, director of quantum and HPC at NVIDIA. “NVIDIA’s quantum computing platform equips pioneers such as AIST, JSC and PSNC to push the boundaries of scientific discovery and advance the state of the art in quantum-integrated supercomputing.”

The QPU integrated with ABCI-Q will enable researchers at AIST to investigate quantum applications in AI, energy and biology, utilizing Rubidium atoms controlled by laser light as qubits to perform calculations. These are the same type of atoms used in precision atomic clocks. Each atom is identical, providing a promising method of achieving a large-scale, high-fidelity quantum processor.

“Japan’s researchers will make progress toward practical quantum computing applications with the ABCI-Q quantum-classical accelerated supercomputer,” said Masahiro Horibe, deputy director of G-QuAT/AIST. “NVIDIA is helping these pioneers push the boundaries of quantum computing research.”

PSNC’s QPUs will enable researchers to explore biology, chemistry and machine learning with two PT-1 quantum photonics systems. The systems use single photons, or packets of light, at telecom frequencies as qubits. This allows for a distributed, scalable and modular quantum architecture using standard, off-the-shelf telecom components.

“Our collaboration with ORCA and NVIDIA has allowed us to create a unique environment and build a new quantum-classical hybrid system at PSNC,” said Krzysztof Kurowski, CTO and deputy director of PSNC. “The open, easy integration and programming of multiple QPUs and GPUs efficiently managed by user-centric services is critical for developers and users. This close collaboration paves the way for a new generation of quantum-accelerated supercomputers for many innovative application areas, not tomorrow, but today.”

The QPU integrated with JUPITER will enable JSC researchers to develop quantum applications for chemical simulations and optimization problems as well as demonstrate how classical supercomputers can be accelerated by quantum computers. It is built with superconducting qubits, or electronic resonant circuits, that can be manufactured to behave as artificial atoms at low temperatures.

“Quantum computing is being brought closer by hybrid quantum-classical accelerated supercomputing,” said Kristel Michielsen, head of the quantum information processing group at JSC. “Through our ongoing collaboration with NVIDIA, JSC’s researchers will advance the fields of quantum computing as well as chemistry and material science.”

By tightly integrating quantum computers with supercomputers, CUDA-Q also enables quantum computing with AI to solve problems such as noisy qubits and develop efficient algorithms.

CUDA-Q is an open-source and QPU-agnostic quantum-classical accelerated supercomputing platform. It is used by the majority of the companies deploying QPUs and delivers best-in-class performance.

About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing.

For further information, contact:
Alex Shapiro
Public Relations
NVIDIA Corporation
+1-415-608-5044
[email protected]

Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, performance, and availability of our products, services, and technologies, including NVIDIA CUDA-Q platform, NVIDIA GH200 Grace Hopper Superchip, and NVIDIA Hopper architecture; NVIDIA accelerating quantum computing efforts at national supercomputing centers around the world with the open-source NVIDIA CUDA-Q platform; third parties using and adopting our technologies and products, our collaboration with third parties and the benefits and impact thereof, and the features, performance and availability of their offerings; useful quantum computing being enabled by the tight integration of quantum with GPU supercomputing; QPU integrated with ABCI-Q enabling researchers at AIST to investigate quantum applications in AI, energy and biology, utilizing Rubidium atoms controlled by laser light as qubits to perform calculations; and Japan’s researchers making progress toward practical quantum computing applications with the ABCI-Q quantum-classical accelerated supercomputer are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners’ products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company’s website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.

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