A Design Framework for the Simulation of Distributed Quantum Computing

• URL: http://arxiv.org/abs/2306.11539v3
• Date: Mon, 22 Apr 2024 14:09:21 GMT
• Title: A Design Framework for the Simulation of Distributed Quantum Computing
• Authors: Davide Ferrari, Michele Amoretti,
• Abstract summary: Growing demand for large-scale quantum computers is pushing research on Distributed Quantum Computing (DQC) Recent experimental efforts have demonstrated some of the building blocks for such a design. DQC systems are clusters of quantum processing units connected by means of quantum network infrastructures.
• Score: 2.969582361376132
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The growing demand for large-scale quantum computers is pushing research on Distributed Quantum Computing (DQC). Recent experimental efforts have demonstrated some of the building blocks for such a design. DQC systems are clusters of quantum processing units (QPUs) connected by means of quantum network infrastructures. Their extension ranges from the single box to the geographical scale. Furthermore, they can be integrated with classical High Performance Computing systems. Simulation modeling of DQC architectures provides a safe way to test and explore different what-if scenarios. Many simulation tools have been developed to support the research community in designing and evaluating quantum computer and quantum network technologies, including hardware, protocols, and applications. However, a framework for DQC simulation putting equal emphasis on computational and networking aspects has never been proposed, so far. In this paper, a design framework for DQC simulation is presented, whose core component is an Execution Manager that schedules DQC jobs for running on networked quantum computers. Two metrics are proposed for evaluating the impact of the job scheduling algorithms with respect to QPU utilization and quantum network utilization, beyond the traditional concept of makespan. The discussion is supported by a DQC job scheduling example, where two different strategies are compared in terms of the proposed metrics.

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