Nvidia Showcases Work with Quantum Centers at ISC 2024

By John Russell

May 13, 2024

With quantum computing surging in Europe, Nvidia took advantage of ISC 2024 to showcase its efforts working with quantum development centers. Currently, Nvidia GPUs are dominant inside classical systems used for quantum simulation and its CUDA-Q platform of tools is gaining tractions.

Nvidia’s ISC anouncment singled out three collaborations:

  • 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.

Tim Costa, director of quantum and HPC at Nvidia said in the formal announcement, “Useful quantum computing will be enabled by the tight integration of quantum with GPU supercomputing. Nvidia 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.”

That message is likely to resonate in Europe, which has been early leader in efforts to integrate quantum computing into traditional advanced computing centers. The EuroHPC JU has plans to develop a network of six quantum computing centers that offer wide access to different types of quantum computing.

Anders Dam Jensen, executive director of the EuroHPC JU told HPCwire in an earlier interview, “The six new EuroHPC quantum computers will be integrated into existing supercomputers, for now functioning as accelerators for specific algorithms, similar to the current role of GPUs, which are able to perform certain operations more efficiently than general purpose processors.

“Such an approach will offer a novel interpretation of quantum computers as accelerator platforms in genuine HPC environments. Bringing this integration to life will of course require essential R&D developments to create a hybrid software stack that can effectively manage both HPC and quantum computing workloads. Additionally, the integration process will benefit from a close collaboration between the HPC operators and European Standardisation bodies.”

One center that’s moved quickly in that area is the JSC. (See HPCwire article, Leibniz QIC’s Mission to Coax Qubits and Bits to Work Together)

It’s noteworthy that Nvidia has been aggressively ramping its quantum computing-related efforts for the past few years. At GTC24, just two months ago, the company had several major announcements (see HPCwire coverage):

  • Nvidia Quantum Cloud. Based on Nvidia’s CUDA-Q platform, Quantum Cloud is a set of microservices for building and testing in the cloud new quantum algorithms and applications — including simulators and tools for hybrid quantum-classical programming. It’s also a place for ISPs to release applications such as one being shown at GTC. Eventually it will include back-end access to third-party quantum hardware.
  • ABCI-Q and Gefion Wins. Being built by Fujitsu at the Japan’s Global Research and Development center for Business byQuantum-AI Technology (G-QuAT) National Institute of Advanced Industrial Science and Technology (AIST), ABCI-Q will be deployed early next year and is designed for integration with future quantum hardware. Gefion is a DGX SuperPod being deployed by Novo Nordisk Foundation Supercomputer for Research in Quantum and Healthcare.
  • cuQPC. This is a new library to accelerate post quantum cryptography algorithms. “What we’re doing is accelerating all the fundamental mathematical primitives which are required underneath these PQC algorithms so that they will run on GPUs at 340 to 515 times faster than they do on CPUs,” said Costa. Nvidia is working with SandboxAQQuSecurePQShield, and Open Quantum Safe, evolutionQ, among others, and cuQPC will be integrated into libqs (git hub) and is part of the newly formed Post-Quantum Cryptography Alliance at The Linux Foundation.
  • CUDA-Q Academic. Aimed at domain experts, CUDA-Q academic is a partnership with a number of universities with whom Nvidia has co-developed with professors who teach quantum computing courses, modules for learning quantum computing using CUDA Q. “So these will be deployed in courses from those professors and also released as an online learning resource by Nvidia — so it’s interactive Jupyter notebooks, lectures, explanations, exercises and assessments, and, of course, will run on GPUs in the cloud,” said Costa.

Costa described Nvidia’s quantum strategy to HPCwire, “What we do is we build a single quantum stack, but we release it in a disaggregated way, so that people who have different needs can intercept that stack at different places. Our products include cu-QUANTUM to accelerate all kinds of quantum simulation, from algorithm design, with circuit simulation down to accurate physics, accurate device modeling and low level simulation for qubit design; DGX Quantum (integrated hw/sw system) to integrate quantum and classical together with very low latency; and CUDA-Q, which is our heterogeneous or integrated quantum-classical platform, including libraries and appropriate model tools and infrastructure for things like error correction.”

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