Presentation
Accelerated Quantum Supercomputing in Action: A Hands-On Tutorial on Scalable Hybrid Workflows
DescriptionAccelerated quantum supercomputing (AQSC) tightly integrates quantum computing with classical accelerated supercomputing via low-latency interconnects. This is crucial for hybrid quantum-classical workflows, enabling scalable quantum algorithms, real-time quantum error correction (QEC), and fast feedback control.
Participants will gain hands-on experience by building hybrid applications using the Python API of CUDA-Q, NVIDIA’s open-source development platform that unifies QPU, CPU, and GPU compute. The primary focus is on scalable hybrid algorithms like the generative quantum eigensolver (GQE), emphasizing AI integration and parallelization. Live demonstrations on NERSC’s Perlmutter supercomputer and Infleqtion’s Sqale neutral-atom QPU will showcase GPU-accelerated workflows. Practical examples include GPU-accelerated decoders and the demonstration of logical qubits using VQE for a material science application. Notebooks for advanced participants will cover algorithms like contextual machine learning (CML), QAOA-GPT, and Auxiliary-Field Quantum Monte Carlo (AFQMC).
Participants will leave with practical skills in building hybrid applications, an understanding of performance-critical AQSC components, and familiarity with emerging techniques in scalable quantum algorithm design. Dedicated compute on Perlmutter and Infleqtion's Sqale simulator/hardware will be provided. The tutorial content will be made public a week before the tutorial: https://github.com/NERSC/SC25-quantum-tutorial.
Participants will gain hands-on experience by building hybrid applications using the Python API of CUDA-Q, NVIDIA’s open-source development platform that unifies QPU, CPU, and GPU compute. The primary focus is on scalable hybrid algorithms like the generative quantum eigensolver (GQE), emphasizing AI integration and parallelization. Live demonstrations on NERSC’s Perlmutter supercomputer and Infleqtion’s Sqale neutral-atom QPU will showcase GPU-accelerated workflows. Practical examples include GPU-accelerated decoders and the demonstration of logical qubits using VQE for a material science application. Notebooks for advanced participants will cover algorithms like contextual machine learning (CML), QAOA-GPT, and Auxiliary-Field Quantum Monte Carlo (AFQMC).
Participants will leave with practical skills in building hybrid applications, an understanding of performance-critical AQSC components, and familiarity with emerging techniques in scalable quantum algorithm design. Dedicated compute on Perlmutter and Infleqtion's Sqale simulator/hardware will be provided. The tutorial content will be made public a week before the tutorial: https://github.com/NERSC/SC25-quantum-tutorial.
Note for Attendees
Please apply for a NERSC training project membership using the link https://forms.gle/AY5EeyMx9GQ3RtQU9 (non-NERSC users due Nov 1, existing NERSC users due Nov 12)
Event Type
Tutorial
TimeSunday, 16 November 20251:30pm - 5:00pm CST
Location124
Livestreamed
Recorded