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Nvidia it’s working with Google Quantum AI to speed up the design of its next-generation quantum computing gadgets utilizing simulations powered by Nvidia.
Google Quantum AI is utilizing the hybrid quantum-classical computing platform and the Nvidia Eos supercomputer to simulate the physics of its quantum processors. This can assist overcome the present limitations of quantum computing {hardware}, which might solely run a sure variety of quantum operations earlier than computations should stop, as a result of what researchers name “noise.”
“The development of commercially useful quantum computers is only possible if we can scale
up quantum hardware while keeping noise in check,” stated Guifre Vidal, analysis scientist from
Google Quantum AI, in an announcement. “Using Nvidia accelerated computing, we’re exploring the noise
implications of increasingly larger quantum chip designs.”
Understanding noise in quantum {hardware} designs requires advanced dynamical simulations able to absolutely capturing how qubits inside a quantum processor work together with their setting.
These simulations have historically been prohibitively computationally costly to pursue. Utilizing the CUDA-Q platform, nevertheless, Google can make use of 1,024 Nvidia H100 Tensor Core GPUs on the Nvidia Eos supercomputer to carry out one of many world’s largest and quickest dynamical simulation of quantum gadgets — at a fraction of the price.
“AI supercomputing power will be helpful to quantum computing’s success,” stated Tim Costa, director of quantum and HPC at Nvidia, in an announcement. “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 carry out absolutely complete, reasonable simulations of gadgets containing 40 qubits – the biggest carried out simulations of this sort. The simulation methods offered by CUDA-Q imply noisy simulations that might’ve taken per week can now run in minutes.
The software program powering these accelerated dynamic simulations might be publicly out there within the CUDA-Q platform, permitting quantum {hardware} engineers to quickly scale their system designs.
