Sunday, August 23, 2026

"Nvidia Bets on the Classical Side of Quantum Computing" (NVDA)

From EE|Times, August 17:

On the ground floor of the Barcelona Supercomputing Center (BSC), MareNostrum 5 sits alongside three new quantum computers housed in an adjoining deconsecrated chapel. The supercomputer, equipped with thousands of Nvidia GPUs, is now connected to the quantum systems. The arrangement puts Nvidia’s role in the emerging hybrid-computing architecture into view.

https://www.eetimes.com/wp-content/uploads/low-260527_capilla_cuantico_04_dsc05683-2.jpg?resize=640%2C427

MareNostrum Ona, the quantum computing partition of MareNostrum 5, is housed in the 
Torre Girona chapel at the Barcelona Supercomputing Center. The red and blue systems 
are the digital quantum computers; the green system in the center is the newly 
inaugurated analog quantum computer. (Source: BSC)

“We don’t build a quantum computer,” said Sam Stanwyck, director of quantum products at Nvidia, in an interview with EE Times. “But Nvidia is fundamentally an accelerated computing platform company, and quantum computing is a part of the future of accelerated computing that we are extremely excited about.”

Nvidia is not developing its own quantum processing units (QPUs). Instead, it is focusing on the classical computing infrastructure around quantum hardware, including software, libraries, interconnects, and control systems that enable hybrid quantum-classical computing. 

Stanwyck compared the company’s hands-off hardware approach to its strategies in other capital-intensive markets. “We don’t build our own robot, but we work with every company that does; we don’t build our own self-driving car, but we work with every company that does; we don’t build our own quantum computer, but we’re working with every company that does to make them successful.”

Integration imperative 
Nvidia’s approach reflects a practical limitation of quantum computing: Quantum processors cannot operate independently. Qubits, the basic units of quantum information, are highly sensitive to noise and errors, requiring classical computing systems to control the hardware, process measurement data, perform error correction, and coordinate workloads....

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