Quantum Accelerators for High-Performance Computing Systems

TL;DR

This paper explores the integration of quantum accelerators into high-performance computing systems, addressing programming challenges, proposing a novel framework, and analyzing system-level performance benefits through simulation.

Contribution

It introduces a new quantum-accelerator framework with specialized kernels and discusses system management, deployment, and performance modeling for hybrid quantum-classical HPC systems.

Findings

Quantum accelerators can improve time-to-solution, accuracy, and energy efficiency.

Simulation results indicate potential performance advantages of quantum acceleration.

System-level behavior can be effectively modeled for hybrid quantum-classical architectures.

Abstract

We define some of the programming and system-level challenges facing the application of quantum processing to high-performance computing. Alongside barriers to physical integration, prominent differences in the execution of quantum and conventional programs challenges the intersection of these computational models. Following a brief overview of the state of the art, we discuss recent advances in programming and execution models for hybrid quantum-classical computing. We discuss a novel quantum-accelerator framework that uses specialized kernels to offload select workloads while integrating with existing computing infrastructure. We elaborate on the role of the host operating system to manage these unique accelerator resources, the prospects for deploying quantum modules, and the requirements placed on the language hierarchy connecting these different system components. We draw on recent advances in the modeling and simulation of quantum computing systems with the development of architectures for hybrid high-performance computing systems and the realization of software stacks for controlling quantum devices. Finally, we present simulation results that describe the expected system-level behavior of high-performance computing systems composed from compute nodes with quantum processing units. We describe performance for these hybrid systems in terms of time-to-solution, accuracy, and energy consumption, and we use simple application examples to estimate the performance advantage of quantum acceleration.