Nvidia Announces Qoda Architecture for Hybrid Quantum-Classical Computing

Noting that many real-world applications of quantum computing actually require a combination of quantum and classical computing, GPU maker Nvidia has introduced the Nvidia Quantum optimized device architecture, which it describes as an open and unified environment for today’s most powerful quantum computers and processors, improving scientific productivity and enabling greater scale in quantum research.

Nvidia Quantum Optimized Device Architecture (Qoda) is expected to accelerate breakthroughs in quantum research and development in AI, HPC, healthcare, finance and other disciplines.

Qoda provides a consistent quantum-classical hybrid programming model for today’s most powerful quantum computers and processors.

“Scientific breakthroughs can happen in the near term with hybrid solutions that combine classical computing and quantum computing,” said Tim Costa, HPC and quantum computing product manager at Nvidia.

“Qoda will revolutionize quantum computing by providing developers with a powerful and productive programming model.”

It provides a single model for C++ and Python programming, he said, and is about 280 times faster than any of today’s leading frameworks when running on the same hardware.

According to the company, Qoda can be used to easily add quantum computing to existing applications, leveraging existing quantum processors or future simulated quantum machines running on Nvidia GPUs currently available in scientific supercomputing centers and public clouds. such as AWS and Azure.

It will initially work with quantum hardware from IQM Quantum Computers, Pasqal, Quantinuum, ANU spinout Quantum Brilliance and Xanadu – all of which use different types of quantum hardware.

“Quantinuum partners with Nvidia to enable users of Quantinuum’s H-series quantum processors, powered by Honeywell, to program and develop the next generation of quantum-classical hybrid applications with Qoda. This combines the most performance to our world-class quantum processors,” said Quantinuum Chief Engineer Alex Chernoguzov.

Other launch partners are software vendors QC Ware and Zapata Computing, and Forschungszentrum Jülich, supercomputing centers at Lawrence Berkeley National Laboratory and Oak Ridge National Laboratory, but Nvidia is “excited to partner with everyone,” Costa pointed out.

Zapata CTO Yudong Cao said, “The hybrid quantum-classical capabilities developed by Nvidia will allow HPC developers to accelerate their existing applications by providing an efficient way to program quantum and classical resources in a consolidated environment.

“Near-term applications in the fields of chemistry, drug discovery, materials science, etc., can now be seamlessly integrated with quantum computing, driving new discoveries in these fields as that practical quantum advantage emerges.”

Kristel Michielsen, Jülich’s Unified Infrastructure Manager for Quantum Computing, said Qoda “helps bring quantum computing closer to the HPC and AI communities.

“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.”

A beta version of Qoda will be available later this year, with general availability expected in early 2023.


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