The Future of Quantum Processors in Supercomputers
The incorporation of quantum processors into the supercomputers of the future is set to greatly expand the range of problems that can be tackled with computing power, revolutionizing industries such as drug development and materials research.
As part of the vision for hybrid quantum-classical supercomputers, accelerated computing is playing a crucial role in advancing the work of quantum researchers and developers. NVIDIA GB200 NVL72 systems, with their fifth-generation multinode NVIDIA NVLink interconnect capabilities, have emerged as the leading architecture in the development of tomorrow's quantum technology. Here are five key quantum computing workloads being developed with the help of NVIDIA Blackwell architecture:
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Developing Better Quantum Algorithms
Simulating how candidate algorithms will perform on quantum computers allows researchers to refine and improve quantum applications. Large-scale simulations carried out with Ansys on DCAI's Gefion supercomputer are aiding in the development of new quantum algorithms for computational fluid dynamics. The high-bandwidth interconnect of GB200 NVL72 is crucial in executing these simulations efficiently, providing an 800x speedup compared to CPU implementations.
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Designing Low-Noise Qubits
Quantum hardware designers are using detailed physics simulations to create low-noise qubit designs, essential for quantum computing. GB200 NVL72, along with cuQuantum's dynamics library, offers a 1,200x speedup for these simulations, accelerating the design process for quantum hardware builders.
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Generating Quantum Training Data
AI models are showing promise in quantum computing challenges, but obtaining the necessary training data can be a hurdle. Simulated quantum processors, powered by GB200 NVL72, can output training data 4,000x faster than CPU-based techniques, facilitating the integration of AI advancements into quantum computing.
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Exploring Hybrid Applications
Future quantum applications will combine quantum and classical hardware, requiring a platform like GB200 NVL72 to explore hybrid algorithms. NVIDIA CUDA-Q provides an ideal environment for researchers to develop hybrid quantum-classical applications, speeding up development by 1,300x.
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Unlocking Quantum Error Correction
Quantum-GPU supercomputers of the future will rely on quantum error correction to continually correct errors. GB200 NVL72 demonstrates a 500x speedup in running decoding algorithms for quantum error correction, making it a feasible prospect for the future of quantum computing.
These advancements are paving the way for the integration of quantum-GPU systems in large-scale quantum computing. Companies like Diraq are already utilizing NVIDIA DGX Quantum reference architecture to connect spins-in-silicon qubits to NVIDIA GPUs. The NVIDIA CUDA-Q Academic program is also enabling researchers to leverage advanced technologies like GB200 NVL72.
NVIDIA is committed to a future where all supercomputers incorporate quantum hardware to address real-world problems. NVIDIA GB200 NVL72 is at the forefront of building this future.
