Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI. learn more
Nvidia is collaborating with Google Quantum AI to accelerate the design of next-generation quantum computing devices using Nvidia simulations.
Google Quantum AI uses a hybrid quantum-classical computing platform and the Nvidia Eos supercomputer to simulate the physics of quantum processors. This could help overcome the current limitations of quantum computing hardware, which can only perform a certain number of quantum operations before stopping calculations, due to what researchers call “noise.”
“Developing commercially useful quantum computers is only possible if they can be scaled.”
It enhances quantum hardware while reducing noise,” said US research scientist Guiffre Vidal.
Google Quantum AI is mentioned in the statement. “We use Nvidia accelerated computing to investigate noise.
The impact of increasingly larger quantum chip designs. ”
Understanding noise in quantum hardware design requires complex dynamic simulations that can fully capture how the qubits in a quantum processor interact with their environment.
These simulations have traditionally been computationally prohibitive to pursue. But by using the CUDA-Q platform, Google is deploying 1,024 Nvidia H100 Tensor Core GPUs on the Nvidia Eos supercomputer to run dynamic simulations of the world’s largest and fastest quantum devices at a fraction of the cost. It can be executed.
“AI’s supercomputing capabilities will help make quantum computing a success,” Tim Costa, director of quantum and HPC at Nvidia, said in a statement. “Google’s use of the CUDA-Q platform demonstrates the central role GPU-accelerated simulation will play in advancing quantum computing to help solve real-world problems.”
Using CUDA-Q and H100 GPUs, Google can run fully comprehensive and realistic simulations of devices containing 40 qubits. This is the largest simulation of its kind. The simulation technology provided by CUDA-Q allows noisy simulations that would normally take a week to run in minutes.
The software that performs these fast dynamic simulations is publicly available on the CUDA-Q platform, allowing quantum hardware engineers to quickly scale their system designs.
