Integrating Quantum Computing Resources into Scientific HPC Ecosystems

TL;DR

This paper presents a hardware-agnostic framework for integrating quantum computing resources into classical HPC systems to enhance scientific research capabilities, leveraging simulators, hardware, and workflows.

Contribution

It introduces a comprehensive framework for augmenting classical HPC with quantum computing, focusing on integration, optimization, and workflow management.

Findings

Benchmarking of quantum accelerators within HPC workflows

Code optimization strategies for quantum-classical hybrid computing

Analysis of quantum noise impact on HPC applications

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.