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

ExpandQISE：轨道 1：迭代和并行量子计算的协作优化和管理

• 批准号: 2329020
• 负责人: Ying Mao
• 金额: $ 69.06万
• 依托单位: Fordham University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-11-15 至 2026-10-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2329020&HistoricalAwards=false
• 关键词: ExpandQISE; Track; Collaborative; Optimization; Management

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.

非技术摘要：量子计算正在迅速发展，从而突破了古典计算的边界。由于任何一台机器上的量子资源有限，最近的研究试图将多个量子机和经典计算节点整合到大规模的多节点系统中。但是，需要针对这些系统进行优化现有的应用程序和管理方案。该项目着眼于迭代和并行的量子应用，研究了旨在充分探索多节点量子古典系统潜力的协作优化和管理方法。拟议的系统以流行的开源项目（例如Qiskit和Kubernetes）为基础，为来自潜水员计算机科学背景的研究人员创建了一个可访问的入口点，以探索量子计算。此外，该团队致力于通过多机构的研讨会和黑客马拉松向代表性不足的学生推广量子计算。这些合作的劳动力发展和能力建设活动将为非R1机构的学生提供开发其量子知识基础的机会，从而在量子计算的新兴领域中为更多样化和熟练的劳动力提供了方向。技术摘要：该项目的研究目的是该项目的研究目标是调查量子系统，可以调查一个可以协作地对量化量的量子量化和平方量的量子应用。所提出的系统将多个量子机与经典计算节点结合在一起，以三种模式运行：仅模拟，仅量子古典和仅量子。具体而言，它支持协作优化，这些优化利用电路分析师自动识别迭代和依赖性操作。它进一步生成了特定于应用程序的逻辑和物理优化计划，以充分利用系统内的可用量子和经典资源。此外，开发了具有可视化表示的协作管理管道。该系统将多个量子和经典节点视为统一系统，并优化了量子和经典计算组件之间的输入输出式往返环回。它利用一种在线途径的组合方法来解决不平衡的执行。此外，它结合了硬件信息的优化和管理，该优化和管理旨在有效地以有效的方式收集硬件的噪声，校准和连接信息，以优化量子应用程序的保真度。它查询硬件以跟踪所需量子算法的重要性参数。最终，该项目提供了一种全面的方法来应对多节点，量子古典系统中所面临的挑战，确保有效的资源利用和无缝集成。该项目由计算机和通信基金会（CCF）部门提供资金。本奖项奖通过评估了NSF的法规范围，反映了NSF的法规范围，并通过评估了其知识范围，并获得了基础的支持。