Discover how to harness CUDA-Q and GPU acceleration for quantum computing, hybrid algorithms, and next-generation quantum hardware.
- Please Note: This event is for The University of Manchester internal staff only
As the era of hybrid quantum-classical computing matures, programming these heterogeneous architectures becomes essential. This course provides a deep dive into CUDA-Q, NVIDIA’s open-source platform for heterogeneous quantum-classical computing. Participants will learn how to leverage GPU acceleration to simulate quantum circuits, develop hybrid algorithms, and prepare for execution on current and future quantum hardware. This course equips the attendees with the tools needed to push the boundaries of quantum simulation and hybrid algorithm design using the industry-leading CUDA-Q platform. The course is intended for computational scientists, quantum algorithm researchers, and software engineers familiar with Python who wish to harness GPU acceleration for quantum computing research.
About the speaker: Esperanza Cuenca Gómez is a developer relations manager for quantum computing at NVIDIA. She has a background in quantum computing, consumer finance, banking and strategy consulting. As an industrial engineer, Esperanza sees applied science and engineering as ways to build new technologies, solve problems and contribute to society.
Schedule
10:00 - 10:15 Arrivals
10:15 - 10:20 Welcome, Tutorial Goals and Schedule
10:20 - 10:35 Accelerated Quantum Supercomputing and CUDA-Q
10:35 - 11:05 Quantum Algorithm Simulations with CUDA-Q - Part 1: Fundamentals
11:05 - 12:00 Quantum Algorithm Simulations with CUDA-Q with CUDA-Q - Part 2: Hands-On Exercise
12:00 - 13:00 Lunch
13:00 - 13:15 AI for Quantum: Overview, Applications and Implications
13:15 - 13:45 GPU-acceleration in Quantum Computing Applications - Part 1: Fundamentals
13:45 - 14:15 Coffee break
14:15 - 15:30 GPU-acceleration in Quantum Computing Applications - Part 2: Hands-On Exercises
15:30 - 16:00 Wrap Up and Takeaways
This event is limited to 30 attendees.
If you register and then can’t attend, please let us know in advance so we can release spaces as needed.
