NVIDIA, Rolls-Royce and Classiq Report Quantum Computing Breakthrough
Quantum circuit for industrial simulation to advance development of quantum computing in aerospace.
Engineering Computing News
Engineering Computing Resources
May 23, 2023
Using NVIDIA’s quantum computing platform, the companies have designed and simulated a large quantum computing circuit for computational fluid dynamics (CFD)—a circuit that measures 10 million layers deep with 39 qubits.
Rolls-Royce plans to use the new circuit on its journey to quantum advantage in CFD for modeling the performance of jet engine designs in simulations that use classical and quantum computing methods.
“Designing jet engines, which are one of the most complicated devices on earth, is expensive and computationally challenging,” says Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA. “NVIDIA’s quantum computing platform gives Rolls-Royce a potential path to tackle these problems head-on while accelerating its research and future development of more efficient jet engines.”
“Applying both classical and quantum computing methods directly to the challenge of designing jet engines will help us accelerate our processes and perform more sophisticated calculations,” says Leigh Lapworth, computational science fellow at Rolls-Royce.
Rolls-Royce and its partner, Israel-based Classiq, designed the circuit using Classiq’s synthesis engine and then simulated it using NVIDIA A100 Tensor Core GPUs. The speed and scale of the process was made possible by NVIDIA cuQuantum, a software development kit that includes optimized libraries and tools to speed up quantum computing workflows.
NVIDIA offers a unified computing platform for speeding breakthroughs in quantum research and development across disciplines. The NVIDIA Grace Hopper Superchip, which combines the performance of NVIDIA Hopper architecture GPUs with NVIDIA Grace CPUs, is ideally designed for large quantum simulation workloads.
Additionally, its high-speed, low-latency NVIDIA NVLink-C2C interconnect makes classical systems built with the superchip optimally suited to link to quantum processors, or QPUs. With a total 600GB of fast-accessible memory per node, Grace Hopper enables the quantum ecosystem to push these simulations to a larger scale.
Grace Hopper powers DGX™ Quantum, a GPU-accelerated quantum computing system combining quantum computing with classical computing. NVIDIA also provides developers with NVIDIA CUDA Quantum, open-source programming model that links GPUs and QPUs.
NVIDIA’s Quantum Ecosystem Expands
An array of quantum computing research now runs on NVIDIA GPUs.
The Jülich Supercomputer Centre, one of Europe’s largest facilities for quantum computing, also announced at ISC plans to build a quantum computing lab with NVIDIA, highlighting the growing importance of hybrid quantum-classical computing systems. The lab will also help developers advance the field of quantum computing with tools like CUDA Quantum.
Additionally, ORCA Computing is the latest QPU builder to integrate CUDA Quantum, combining its photonic quantum computer with GPUs for machine learning. TensorFlow Quantum and TorchQuantum—two quantum machine learning frameworks—now also integrate cuQuantum. The majority of quantum computing software supports GPU acceleration with the NVIDIA quantum platform.
Sources: Press materials received from the company and additional information gleaned from the company’s website.
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