Integrating Quantum Computing Resources into Scientific HPC Ecosystems

TL;DR

This paper addresses the challenge of leveraging quantum computing to accelerate classical HPC workloads in the NISQ era by proposing a hardware-agnostic QC/HPC integration framework (QFw). It details a multi-layer architecture including a Quantum Task Manager (QTM) and Quantum Platform Manager (QPM), a dynamic simulation environment, and end-to-end workflows to couple quantum circuits with HPC tasks, tested against on-premises and cloud-compatible backends. It surveys current QC/HPC activity, outlines a plan for hardware-software co-design, benchmarking, and user engagement, and presents prototypes that integrate simulators (e.g., TN-QVM, NWQ-Sim, ExaTN) with HPC resources under a scalable resource-management model. The work aims to enable near-term quantum acceleration for DOE/ORNL mission-relevant problems, drive standards for interoperability and benchmarking, and lay groundwork for scalable, on-premises quantum data centers and future quantum networking.

Abstract

Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era's inherent external noise issues. This paper discusses the integration of QC as a computational accelerator within classical scientific high-performance computing (HPC) systems. By leveraging a broad spectrum of simulators and hardware technologies, we propose a hardware-agnostic framework for augmenting classical HPC with QC capabilities. Drawing on the HPC expertise of the Oak Ridge National Laboratory (ORNL) and the HPC lifecycle management of the Department of Energy (DOE), our approach focuses on the strategic incorporation of QC capabilities and acceleration into existing scientific HPC workflows. This includes detailed analyses, benchmarks, and code optimization driven by the needs of the DOE and ORNL missions. Our comprehensive framework integrates hardware, software, workflows, and user interfaces to foster a synergistic environment for quantum and classical computing research. This paper outlines plans to unlock new computational possibilities, driving forward scientific inquiry and innovation in a wide array of research domains.

Figures (4)

• Figure 1: The QC/HPC Integration Framework uses a layered approach, with a quantum-aware resource management system reserving resources. Applications run on these resources and communicate quantum operations via MPI through the Quantum Task Manager, which can modify tasks, such as by circuit cutting. The Quantum Platform Manager then executes the prepared tasks on the quantum platform. Blue boxes represent classical resources, while orange boxes denote quantum resources.
• Figure 2: Schematic of the QC/HPC integration at OLCF. This is a high-level view of the ideal state of the framework presented in Section \ref{['sec:integrationFramework']}. The framework will integrate simulators, cloud-based quantum devices, and on-premises quantum hardware in a seamless way.
• Figure 3: Schematic showing how the TN-QVM, an ORNL-developed tensor-network based accelerator, integrates with various other software packages to form a powerful tool for simulating large circuits and algorithms on HPC platforms.
• Figure 4: The dynamic simulation environment is composed of a set of classical HPC nodes. It can be partitioned into separate sets for running different types of quantum simulators. See also discussion in Sec. \ref{['ssec:simulators']})