Quantum Application Development with CUDA-Q

LANL is hosting a Quantum Application Development with CUDA-Q Training, presented by Monica VanDieren from Nvidia. This event is open to NERSC users. 

Description

Future practical quantum computing depends on seamlessly integrating classical and quantum resources. CUDA-Q provides a unified programming model tailored for a hybrid setting — that is, CPUs, GPUs, and QPUs working together. This interactive workshop introduces CUDA-Q, equipping researchers, developers, and domain scientists with the skills to develop and scale hybrid quantum-classical applications and advance quantum research.

Topics Covered

• CUDA-Q Basics
• Options for GPU-accelerated quantum simulation including
  • Single and multi-node, multi-GPU
  • MPS and Tensor Network simulators
  • Noisy Simulators
  • Multi-QPU Simulators
• CUDA-QX Libraries for Quantum Error Correction and Application Development
• Dynamics Simulation

Prerequisites

Familiarity with Python and Jupyter notebooks. Basic understanding of quantum computing concepts, such as quantum circuits. Familiarity with variational quantum algorithms, noisy models, and more advanced quantum computing concepts is helpful, but not required.

Speaker Bio

As a Senior Technical Marketing Engineer at NVIDIA, Monica VanDieren specializes in quantum and high-performance computing, driving initiatives such as the CUDA-Q Academic program. Before joining NVIDIA, Monica worked on IBM’s Quantum Accelerator programs. With a Ph.D. in Mathematical Sciences from Carnegie Mellon University, she brings over 20 years of academic experience at universities such as Stanford, the University of Michigan, and Robert Morris University to her work.