Pilot-Quantum: A Quantum-HPC Middleware for Resource, Workload and Task Management

December 24, 2024 Β· Declared Dead Β· πŸ› IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing

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Authors Pradeep Mantha, Florian J. Kiwit, Nishant Saurabh, Shantenu Jha, Andre Luckow arXiv ID 2412.18519 Category quant-ph: Quantum Computing Cross-listed cs.DC, cs.ET Citations 4 Venue IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing Last Checked 5 months ago
Abstract
As quantum hardware advances, integrating quantum processing units (QPUs) into HPC environments and managing diverse infrastructure and software stacks becomes increasingly essential. Pilot-Quantum addresses these challenges as a middleware designed to provide unified application-level management of resources and workloads across hybrid quantum-classical environments. It is built on a rigorous analysis of existing quantum middleware systems and application execution patterns. It implements the Pilot Abstraction conceptual model, originally developed for HPC, to manage resources, workloads, and tasks. It is designed for quantum applications that rely on task parallelism, including (i) hybrid algorithms, such as variational approaches, and (ii) circuit cutting systems, used to partition and execute large quantum circuits. Pilot-Quantum facilitates seamless integration of QPUs, classical CPUs, and GPUs, while supporting high-level programming frameworks like Qiskit and Pennylane. This enables users to efficiently design and execute hybrid workflows across diverse computing resources. The capabilities of Pilot-Quantum are demonstrated through mini-apps -- simplified yet representative kernels focusing on critical performance bottlenecks. We demonstrate the capabilities of Pilot-Quantum through multiple mini-apps, including different circuit executions (e.g., using IBMΕ› Eagle QPU and simulators), circuit cutting, and quantum machine learning scenarios.
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