Dynamic Solutions for Hybrid Quantum-HPC Resource Allocation

TL;DR

This paper proposes a malleability-based and workflow strategy for dynamic resource allocation in hybrid HPC-quantum systems, improving efficiency by reallocating classical resources during quantum tasks.

Contribution

It introduces novel approaches to optimize resource utilization in hybrid HPC-quantum workloads, addressing key technical challenges.

Findings

Dynamic allocation improves resource efficiency in hybrid workloads.

Experiments demonstrate benefits of reallocating classical resources during quantum processing.

Proposed methods facilitate better integration of quantum accelerators in HPC environments.

Abstract

The integration of quantum computers within classical High-Performance Computing (HPC) infrastructures is receiving increasing attention, with the former expected to serve as accelerators for specific computational tasks. However, combining HPC and quantum computers presents significant technical challenges, including resource allocation. This paper presents a novel malleability-based approach, alongside a workflow-based strategy, to optimize resource utilization in hybrid HPC-quantum workloads. With both these approaches, we can release classical resources when computations are offloaded to the quantum computer and reallocate them once quantum processing is complete. Our experiments with a hybrid HPC-quantum use case show the benefits of dynamic allocation, highlighting the potential of those solutions.