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Q-GPU: A Recipe of Optimizations for Quantum Circuit Simulation Using GPUs

Tang, Xulong (2022) Q-GPU: A Recipe of Optimizations for Quantum Circuit Simulation Using GPUs. In: Pitt Momentum Fund 2022.

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Abstract

In recent years, quantum computing has undergone significant developments and has established its supremacy in many application domains. While quantum hardware is accessible to the public through the cloud environment, a robust and efficient quantum circuit simulator is necessary to investigate the constraints and foster quantum computing development, such as quantum algorithm development and quantum device architecture exploration. In this project, we propose to systematically investigate the deficiencies in quantum circuit simulation (QCS) and propose Q-GPU, a framework that leverages GPUs with comprehensive optimizations to allow efficient and scalable QCS.


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Details

Item Type: Conference or Workshop Item (Other)
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Tang, XulongTAX6@pitt.edu0000-0002-3385-2053
Centers: Other Centers, Institutes, Offices, or Units > Office of Sponsored Research > Pitt Momentum Fund
Date: 2022
Event Title: Pitt Momentum Fund 2022
Event Type: Other
DOI or Unique Handle: 10.18117/v3zy-5614
Schools and Programs: School of Computing and Information > Computer Science
Refereed: No
Uncontrolled Keywords: Seeding Grants - Engineering, Technology, Natural Sciences, and Mathematical Sciences
Date Deposited: 07 Mar 2022 19:58
Last Modified: 07 Mar 2022 19:58
URI: http://d-scholarship.pitt.edu/id/eprint/42319

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