NVIDIA Accelerates Google Quantum AI Processor Design With Simulation of Quantum Device Physics
NVIDIA announced a collaboration with Google Quantum AI to accelerate quantum computing device design using the NVIDIA CUDA-Q™ platform and Eos supercomputer. The partnership aims to simulate quantum processor physics to address noise limitations in quantum computing hardware.
Using 1,024 NVIDIA H100 Tensor Core GPUs, Google can now perform one of the world's largest dynamical simulations of quantum devices, capable of simulating 40 qubits. The CUDA-Q platform has significantly reduced simulation time from weeks to minutes, and the software will be made publicly available for quantum hardware engineers.
NVIDIA ha annunciato una collaborazione con Google Quantum AI per accelerare la progettazione di dispositivi di calcolo quantistico utilizzando la piattaforma NVIDIA CUDA-Q™ e il supercomputer Eos. L'obiettivo della partnership è simulare la fisica dei processori quantistici per affrontare le limitazioni del rumore nell'hardware di calcolo quantistico.
Utilizzando 1.024 GPU NVIDIA H100 Tensor Core, Google può ora eseguire una delle simulazioni dinamiche più grandi al mondo di dispositivi quantistici, in grado di simulare 40 qubit. La piattaforma CUDA-Q ha ridotto significativamente il tempo di simulazione da settimane a minuti, e il software sarà reso disponibile pubblicamente per gli ingegneri dell'hardware quantistico.
NVIDIA anunció una colaboración con Google Quantum AI para acelerar el diseño de dispositivos de computación cuántica utilizando la plataforma NVIDIA CUDA-Q™ y el superordenador Eos. La asociación tiene como objetivo simular la física de los procesadores cuánticos para abordar las limitaciones de ruido en el hardware de computación cuántica.
Usando 1,024 GPUs NVIDIA H100 Tensor Core, Google ahora puede realizar una de las simulaciones dinámicas más grandes del mundo de dispositivos cuánticos, capaz de simular 40 qubits. La plataforma CUDA-Q ha reducido significativamente el tiempo de simulación de semanas a minutos, y el software estará disponible públicamente para los ingenieros de hardware cuántico.
NVIDIA는 NVIDIA CUDA-Q™ 플랫폼과 Eos 슈퍼컴퓨터를 사용하여 양자 컴퓨팅 장치 설계를 가속화하기 위해 Google Quantum AI와 협력한다고 발표했습니다. 이 파트너십의 목표는 양자 컴퓨팅 하드웨어에서 노이즈 제한을 해결하기 위해 양자 프로세서 물리학을 시뮬레이션하는 것입니다.
1,024개의 NVIDIA H100 텐서 코어 GPU를 사용하여 Google은 이제 40 큐비트를 시뮬레이션할 수 있는 세계에서 가장 큰 양자 장치 동적 시뮬레이션 중 하나를 수행할 수 있습니다. CUDA-Q 플랫폼은 시뮬레이션 시간을 주에서 분으로 크게 줄였으며, 소프트웨어는 양자 하드웨어 엔지니어를 위해 공개될 예정입니다.
NVIDIA a annoncé une collaboration avec Google Quantum AI pour accélérer la conception de dispositifs de calcul quantique en utilisant la plateforme NVIDIA CUDA-Q™ et le superordinateur Eos. L'objectif du partenariat est de simuler la physique des processeurs quantiques afin de traiter les limitations de bruit dans le matériel de calcul quantique.
En utilisant 1 024 GPU NVIDIA H100 Tensor Core, Google peut maintenant réaliser l'une des plus grandes simulations dynamiques de dispositifs quantiques au monde, capable de simuler 40 qubits. La plateforme CUDA-Q a considérablement réduit le temps de simulation de semaines à minutes, et le logiciel sera rendu disponible au public pour les ingénieurs en matériel quantique.
NVIDIA hat eine Zusammenarbeit mit Google Quantum AI angekündigt, um das Design von quantencomputing Geräten mit der NVIDIA CUDA-Q™ Plattform und dem Eos Supercomputer zu beschleunigen. Ziel der Partnerschaft ist es, die Physik von Quantenprozessoren zu simulieren, um die Rauschbeschränkungen in der quantencomputing Hardware zu adressieren.
Mit 1.024 NVIDIA H100 Tensor Core GPUs kann Google nun eine der größten dynamischen Simulationen von Quantengeräten weltweit durchführen, die in der Lage ist, 40 Qubits zu simulieren. Die CUDA-Q Plattform hat die Simulationszeit erheblich von Wochen auf Minuten verkürzt, und die Software wird öffentlich für Ingenieure in der Quantenhardware zur Verfügung stehen.
- Enables simulation of 40 qubits, marking the largest-performed simulations of this kind
- Reduces simulation time from one week to minutes
- Software will be publicly available, expanding market reach
- Leverages 1,024 NVIDIA H100 Tensor Core GPUs for quantum simulations
- None.
Insights
The collaboration between NVIDIA and Google Quantum AI represents a significant technological breakthrough in quantum computing development. Using NVIDIA's H100 GPUs and CUDA-Q platform to simulate 40-qubit devices marks a 1000x acceleration in simulation speed - reducing week-long processes to minutes. This capability directly addresses the critical "noise" challenge in quantum computing.
The public availability of this simulation software through CUDA-Q will accelerate industry-wide quantum hardware development. For NVIDIA investors, this strengthens the company's position in the emerging quantum computing market, particularly in the important simulation and development tools segment. The partnership with Google Quantum AI validates NVIDIA's quantum strategy and demonstrates another high-value application for its H100 GPUs.
NVIDIA CUDA-Q Platform Enables Google Quantum AI Researchers to Create Massive Digital Model of Its Quantum Computer to Solve Design Challenges
ATLANTA, Nov. 18, 2024 (GLOBE NEWSWIRE) -- SC24 -- NVIDIA today announced it is working with Google Quantum AI to accelerate the design of its next-generation quantum computing devices using simulations powered by the NVIDIA CUDA-Q™ platform.
Google Quantum AI is using the hybrid quantum-classical computing platform and the NVIDIA Eos supercomputer to simulate the physics of its quantum processors. This will help overcome the current limitations of quantum computing hardware, which can only run a certain number of quantum operations before computations must cease, due to what researchers call “noise.”
“The development of commercially useful quantum computers is only possible if we can scale up quantum hardware while keeping noise in check,” said Guifre Vidal, research scientist from Google Quantum AI. “Using NVIDIA accelerated computing, we’re exploring the noise implications of increasingly larger quantum chip designs.”
Understanding noise in quantum hardware designs requires complex dynamical simulations capable of fully capturing how qubits within a quantum processor interact with their environment.
These simulations have traditionally been prohibitively computationally expensive to pursue. Using the CUDA-Q platform, however, Google can employ 1,024 NVIDIA H100 Tensor Core GPUs at the NVIDIA Eos supercomputer to perform one of the world’s largest and fastest dynamical simulation of quantum devices — at a fraction of the cost.
“AI supercomputing power will be helpful to quantum computing’s success,” said Tim Costa, director of quantum and HPC at NVIDIA. “Google’s use of the CUDA-Q platform demonstrates the central role GPU-accelerated simulations have in advancing quantum computing to help solve real-world problems.”
With CUDA-Q and H100 GPUs, Google can perform fully comprehensive, realistic simulations of devices containing 40 qubits — the largest-performed simulations of this kind. The simulation techniques provided by CUDA-Q mean noisy simulations that would have taken a week can now run in minutes.
The software powering these accelerated dynamic simulations will be publicly available in the CUDA-Q platform, allowing quantum hardware engineers to rapidly scale their system designs.
About NVIDIA
NVIDIA (NASDAQ: NVDA) is the world leader in accelerated computing.
For further information, contact:
Cliff Edwards
NVIDIA Corporation
+1-415-699-2755
cliffe@nvidia.com
Certain statements in this press release including, but not limited to, statements as to: the benefits, impact, and performance of NVIDIA’s products, services, and technologies, including NVIDIA CUDA-Q platform, NVIDIA Eos supercomputer, and NVIDIA H100 Tensor Core GPUs; Google using our products and technologies, the benefits and impact thereof, and the features, performance and availability of its offerings; and AI supercomputing power being helpful to quantum computing’s success are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expectations. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; the impact of technological development and competition; development of new products and technologies or enhancements to our existing product and technologies; market acceptance of our products or our partners' products; design, manufacturing or software defects; changes in consumer preferences or demands; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors detailed from time to time in the most recent reports NVIDIA files with the Securities and Exchange Commission, or SEC, including, but not limited to, its annual report on Form 10-K and quarterly reports on Form 10-Q. Copies of reports filed with the SEC are posted on the company's website and are available from NVIDIA without charge. These forward-looking statements are not guarantees of future performance and speak only as of the date hereof, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
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FAQ
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