ExpandQISE: Track 1: Collaborative Optimization and Management for Iterative and Parallel Quantum Computing

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Non-technical Abstract: Quantum computing is advancing rapidly, pushing the boundaries of classical computing. Due to limited quantum resources on any single machine, recent research attempts to integrate multiple quantum machines and classical computing nodes into large-scale, multi-node systems. However, existing applications and management schemes need to be optimized with respect to these systems. Focusing on iterative and parallel quantum applications, this project studies collaborative optimizations and management approaches that aim to fully exploit the potential of a multi-node quantum-classical system. Building on popular open-source projects, such as Qiskit and Kubernetes, the proposed system creates an accessible entry point for researchers from diverse computer science backgrounds to explore quantum computing. Moreover, the team is committed to promoting quantum computing to underrepresented students through multi-institutional workshops and hackathons. These collaborative workforce developments and capacity-building activities will provide opportunities for students at a non-R1 institution to develop their quantum knowledge base, paving the way for a more diverse and skilled workforce in the emerging field of quantum computing.Technical Abstract: The research objective of this project is to investigate a quantum-classical system that can collaboratively optimize iterative and parallel quantum applications. The proposed system combines multiple quantum machines with classical computing nodes, operating in three modes: simulation-only, quantum-classical, and quantum-only. Specifically, it supports collaborative optimizations which utilize a circuit analyst to identify iterative and dependent operations automatically. It further generates application-specific logical and physical optimization plans to fully leverage the available quantum and classical resources within the system. Additionally, a collaborative management pipeline is developed with a visualized representation. The system considers multiple quantum and classical nodes as a unified system and optimizes input-output roundtrip loopback between quantum and classical computing components. It utilizes an online-offline combined approach to address the imbalanced executions. Furthermore, it incorporates hardware-informed optimization and management, which seeks to effectively gather the hardware’s noise, calibration, and connectivity information in an efficient way to optimize the quantum application’s fidelity. It queries the hardware to track parameters of importance to the desired quantum algorithm. Ultimately, this project provides a comprehensive approach to tackling the challenges faced in multi-node, quantum-classical systems, ensuring efficient resource utilization and seamless integration.This project is funded by The Computing and Communications Foundations (CCF) Division.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.