CUDA Quantum: The Platform for Integrated Quantum-Classical Computing

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 c...

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Vydáno v:2023 60th ACM/IEEE Design Automation Conference (DAC) s. 1 - 4
Hlavní autoři: Kim, Jin-Sung, McCaskey, Alex, Heim, Bettina, Modani, Manish, Stanwyck, Sam, Costa, Timothy
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 09.07.2023
Témata:
Computational modeling
Computers
Electric potential
Graphics processing units
HPC
hybrid quantum classical
Parallel programming
Quantum computing
Software algorithms
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Shrnutí: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.
DOI:10.1109/DAC56929.2023.10247886