CUDA Quantum: The Platform for Integrated Quantum-Classical Computing

被引:4
作者
Kim, Jin-Sung [1 ]
McCaskey, Alex [1 ]
Heim, Bettina [1 ]
Modani, Manish [1 ]
Stanwyck, Sam [1 ]
Costa, Timothy [1 ]
机构
[1] NVIDIA, Santa Clara, CA 95051 USA
来源
2023 60TH ACM/IEEE DESIGN AUTOMATION CONFERENCE, DAC | 2023年
关键词
Quantum computing; hybrid quantum classical; HPC;
D O I
10.1109/DAC56929.2023.10247886
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A critical challenge to making quantum computers work in practice is effectively combining them with classical computing resources. From the classical side of hybrid algorithms and integrated application workflows to decoding syndromes for quantum error correction, tightly coupled high performance classical computing will be important for many of the functions required to realize useful quantum computing. A key tool for enabling 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. NVIDIA 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, we present CUDA Quantum and demonstrate several use cases including Variational Quantum Eigensolver (VQE) where it provides a significant (287x) performance and capability benefit over existing quantum programming.
引用
收藏
页数:4
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