NVIDIA and Google Quantum AI are pushing the boundaries of quantum computing by leveraging the NVIDIA CUDA-Q platform to accelerate the design of next-generation quantum devices.
Google Quantum AI is harnessing the power of NVIDIA’s hybrid quantum-classical computing platform and the Eos supercomputer to simulate the intricate physics of its quantum processors.
With this approach, it aims to shatter the current barriers in quantum computing hardware, which is plagued by ‘noise’ – a phenomenon that forces computations to halt after a limited number of quantum operations.
By leveraging these advanced simulation capabilities, researchers are poised to extend the operational lifespan of quantum computations to potentially unlock a new era of quantum problem-solving.
“The development of commercially useful quantum computers is only possible if we can scale up quantum hardware while keeping noise in check. Using NVIDIA accelerated computing, we are exploring the noise implications of increasingly larger quantum chip designs,” said Guifre Vidal, Research Scientist of Google Quantum AI.
To improve quantum computers, scientists need to understand how ‘noise’ affects them. Imagine trying to listen to a whisper in a noisy room — that’s similar to the challenge quantum computers face.
To study this, researchers use complex computer simulations that show how the basic units of quantum computers (called qubits) interact with their surroundings.
In the past, these simulations were extremely time-consuming and expensive to run. But using NVIDIA’s CUDA-Q system and the Eos supercomputer dramatically speeds up the process and reduces costs..
This setup involves 1,024 NVIDIA’s H100 chips working together to focus on on a problem. As a result, Google can now run some of the world’s largest and fastest simulations of quantum devices, and do it much more affordably than ever before. The simulation techniques provided by CUDA-Q mean noisy simulations that would have taken a week can now run in minutes.
“AI supercomputing power will be helpful to quantum computing’s success. 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,” said Tim Costa, Director of Quantum and HPC at NVIDIA.
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