In addition to conventional computing adopting NVIDIA Grace-Hopper Superchips for enhanced supercomputing performance, the quantum computing sector is also leveraging these chips through NVIDIA’s CUDA-Q platform.

NVIDIA Quantum Computing CUDA Q

Specifically, institutions in Germany, Japan, and Poland are using NVIDIA’s hardware and software to power Quantum Processing Units (QPUs) for significant advancements in data processing.

Germany’s Jülich Supercomputing Centre (JSC) will integrate a QPU from IQM Quantum Computers with its GH200-supercharged system, adding it as a module to the JUPITER Supercomputer for applications like chemical simulations and optimization workflows enabled by superconducting qubits.

In Japan, the ABCI-Q supercomputer at the National Institute of Advanced Industrial Science and Technology (AIST) will implement QuEra’s QPU, aiming to accelerate developments in AI-based quantum applications, energy, and biology breakthroughs using Rubidium atoms controlled by laser light as qubits.

Poland’s Poznan Supercomputing and Networking Center (PSNC) will deploy two photonic QPUs from ORCA Computing, integrated with a new supercomputer partition enhanced by NVIDIA Hopper. These PT-1 quantum photonics systems use telecom frequencies as qubits, allowing scalable and modular architecture with off-the-shelf telecom equipment. Targeted fields selected by the researchers include biology, chemistry, and machine learning.

Beyond addressing specific fields of study, NVIDIA believes its CUDA-Q platform can also leverage AI to resolve challenges in quantum computing, such as noisy qubits and the development of efficient algorithms for improved outcomes.

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