University of Kwazulu-Natal

Nvidia Partners Accelerate Quantum Breakthroughs With Ai Supercomputin

Bonisiwe Shabane
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nvidia partners accelerate quantum breakthroughs with ai supercomputin

May 19, 2025 00:43 ET | Source: NVIDIA NVIDIA TAIPEI, Taiwan, May 19, 2025 (GLOBE NEWSWIRE) -- COMPUTEX — NVIDIA today announced the opening of the Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT), which hosts ABCI-Q — the world’s... Quantum processors promise to augment AI supercomputers in solving some of the world’s most complex challenges, spanning industries including healthcare, energy and finance. By enabling quantum-GPU computing at an unprecedented scale, ABCI-Q marks a profound leap toward realizing practical, accelerated quantum systems. Delivered by Japan’s National Institute of Advanced Industrial Science and Technology (AIST), the ABCI-Q supercomputer features 2,020 NVIDIA H100 GPUs interconnected by the NVIDIA Quantum-2 InfiniBand networking platform. The system is integrated with NVIDIA CUDA-Q™, an open-source hybrid computing platform for orchestrating the hardware and software needed to run useful, massive-scale quantum computing applications.

Quantum computers have the potential to revolutionize fields like energy and materials science. But their basic building blocks—qubits—are currently extremely fragile and can lose their information from even the slightest disturbances like heat, stray electromagnetic signals, or vibrations. That’s why, in the near term, real breakthroughs in quantum computing will depend on correcting errors, requiring that quantum devices work in tandem with today’s most powerful traditional computing resources, such as high-performance computers... This NVQLink partnership was announced on Tuesday, October 28, at the NVIDIA GPU Technology Conference in Washington, D.C. The collaboration will leverage Berkeley Lab’s Quantum bit Controller (QubiC) to run hybrid applications on Quantum Processing Units (QPUs), Graphics Processing Units (GPUs), and Central Processing Units (CPUs) as needed. When QPUs, GPUs, CPUs, and their control systems are tightly connected and can exchange data quickly and in large amounts, developers can tackle the heavy computational demands of quantum error correction—a process that detects...

“QubiC is one of the first open-source platforms to tightly integrate quantum hardware control, hybrid quantum-classical workflows, and high-performance computing in a modular, extensible way,” said Gang Huang, a staff scientist in Berkeley Lab’s... “By focusing on open access and seamless orchestration of QPUs, GPUs, and CPUs within supercomputing environments, our NVQlink partnership is setting a new standard for collaborative, scalable, and accessible quantum research.” “By incorporating QubiC into NVQlink, we will provide researchers with open access to the tools and infrastructure needed for rapid innovation,” said Yilun Xu, a research scientist in Berkeley Lab’s ATAP Division who is... “This quantum ecosystem—including integration with HPC—allows scientists to tackle critical challenges like error correction and hybrid algorithms at scale, helping the entire research community move faster toward reliable, real-world quantum computers.” Quantum computing’s promise has long rested on a single, stubborn question: how do you scale fragile qubits into something useful? Quantinuum and Nvidia believe the answer lies in coupling error-corrected quantum processors with GPU-powered AI supercomputers' raw, parallel horsepower.

Their new collaboration, centred on the Nvidia Accelerated Quantum Research Center (NVAQC) in Boston, aims to create “accelerated quantum supercomputers” capable of overcoming qubit noise, algorithmic instability, and other roadblocks that have kept quantum... "AI and quantum will be essential for each other, and it’s a two-way street," said Mark Jackson, senior quantum evangelist at Quantinuum. In practice, that means using deep-learning models to optimise quantum compilers today while preparing quantum processors to supercharge AI workloads tomorrow—an approach the partners hope will turn niche demonstrations into mainstream tools. Announced in March 2025, the NVAQC opened with a remit to merge best-in-class quantum hardware, error-mitigation software, and Nvidia’s CUDA-Quantum framework. The centre is designed to move quantum computing out of the lab and into commercial reality by providing a neutral sandbox for device makers, algorithm developers, and academic theorists. NVIDIA’s vision of accelerated quantum supercomputers integrates quantum hardware and AI supercomputing to turn today’s quantum processors into tomorrow’s useful quantum computing devices.

At Supercomputing 2024 (SC24), NVIDIA announced a wave of projects with partners that are driving the quantum ecosystem through those challenges standing between today’s technologies and this accelerated quantum supercomputing. This post highlights these projects, which span quantum hardware, algorithms, and system integrations. Generative AI is one of the most promising tools for addressing the challenges facing quantum computing. NVIDIA has partnered with scientists from industry and academia to release the new review research paper, Artificial Intelligence for Quantum Computing, outlining how AI is set to change quantum computing (Figure 1). Focusing on topics such as using GPT models to synthesize quantum circuits, and transformers to decode QEC codes, the paper surveys critical work occurring at the intersection of two of computing’s most transformational disciplines. Poznan Supercomputing and Networking Center (PSNC) and ORCA Computing announced results from an AI for quantum collaboration with NVIDIA.

The team demonstrated the first fully functional multi-QPU, multi-GPU, multi-user infrastructure by leveraging NVIDIA H100 Tensor Core GPUs, the NVIDIA CUDA-Q platform, and two ORCA PT-1 photonic quantum computers. As quantum computers continue to develop, they will integrate with AI supercomputers to form accelerated quantum supercomputers capable of solving some of the world’s hardest problems. Integrating quantum processing units (QPUs) into AI supercomputers is key for developing new applications, helping unlock breakthroughs critical to running future quantum hardware and enabling developments in quantum error correction and device control. The NVIDIA Accelerated Quantum Research Center, or NVAQC, announced today at the NVIDIA GTC global AI conference, is where these developments will happen. With an NVIDIA GB200 NVL72 system and the NVIDIA Quantum-2 InfiniBand networking platform, the facility will house a supercomputer with 576 NVIDIA Blackwell GPUs dedicated to quantum computing research. “The NVAQC draws on much-needed and long-sought-after tools for scaling quantum computing to next-generation devices,” said Tim Costa, senior director of computer-aided engineering, quantum and CUDA-X at NVIDIA.

“The center will be a place for large-scale simulations of quantum algorithms and hardware, tight integration of quantum processors, and both training and deployment of AI models for quantum.” Quantum computing innovators like Quantinuum, QuEra and Quantum Machines, along with academic partners from the Harvard Quantum Initiative and the Engineering Quantum Systems group at the MIT Center for Quantum Engineering, will work on... NVIDIA CEO Jensen Huang kicked off Computex 2025 in Taipei with a bold vision for an AI-driven future. He emphasized that AI is now fundamental infrastructure, likening it to electricity and the internet, and described how AI data centers are evolving into “AI factories” that generate valuable tokens. “They’re not data centers of the past,” Huang explained. “These AI data centers, if you will, are improperly described.

They are, in fact, AI factories. You apply energy to it, and it produces something incredibly valuable, and these things are called tokens.” Huang showcased NVIDIA’s CUDA-X platform, highlighting its role in advancing AI, 6G, and quantum supercomputing. He outlined the growing power of AI, leading to “agentic AI,” which can think and act, and “physical AI,” which understands the world—culminating in general robotics. To meet surging demand, Huang announced innovations such as NVIDIA Blackwell-powered systems, NVLink Fusion to optimise AI data centers, and collaborations with major global tech players. He also detailed NVIDIA’s partnership with Taiwan, including an AI supercomputer project with Foxconn and the Taiwan government.

New product announcements included DGX Spark, a personal AI supercomputer; DGX Station, capable of running trillion-parameter models; NVIDIA RTX PRO Servers for enterprise AI; and NVIDIA AI Data Platform for intelligent storage. He also introduced tools for humanoid robotics, including Isaac GR00T-Dreams and the GR00T N1.5 foundation model.

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