Integrated Quantum: Classical Applications with CUDA Quantum

(27:48 + Q&A) Dr. Jin-Sung Kim, NVIDIA -- Presentation from 2023 Workshop on Quantum Computing: Devices, Cryogenic Electronics and Packaging (QC-DCEP) ... 
Summary: A critical challenge to leveraging the computational advantages of a future quantum processor is to effectively combine it with the best existing classical computing infrastructure. A key tool for enabling hybrid quantum-classical research and application development is a programming model and software toolchain which allow researchers to straightforwardly co-program classical and quantum computers and leverage the best tools available for each. CUDA Quantum is a single-source programming model in C++ and Python for heterogeneous quantum-classical computing. The CUDA Quantum platform provides several advantages and new capabilities that enable users to get more out of quantum processors. Here, CUDA Quantum is discussed in the context of a quantum chemistry application, the Variational Quantum Eigensolver (VQE) where it provides a significant (~287x) performance and capability benefit over existing quantum programming paradigms.
Jin-Sung Kim is the Developer Relations Manager for Quantum Computing at NVIDIA and is based out of San Francisco. In his current role, he manages partnerships, technical collaborations and the rapidly growing NVIDIA Quantum ecosystem. Prior to NVIDIA, he was a Research Staff Member at IBM Quantum. Jin-Sung holds a PhD from Princeton University.

Additional videos from the QC-DCEP Workhop can be accessed at https://attend.ieee.org/qc-dcep.