Load balancing for high performance computing using quantum annealing

Rathore, Omer; Basden, Alastair; Chancellor, Nicholas; Kusumaatmaja, Halim

Abstract

With the advent of exascale computing, effective load balancing in massively parallel software applications is critically important for leveraging the full potential of high-performance computing systems. Load balancing is the distribution of computational work between available processors. Here, we investigate the application of quantum annealing to load balance two paradigmatic algorithms in high-performance computing. Namely, adaptive mesh refinement and smoothed particle hydrodynamics are chosen as representative grid and off-grid target applications. While the methodology for obtaining real simulation data to partition is application specific, the proposed balancing protocol itself remains completely general. In a grid based context, quantum annealing is found to outperform classical methods such as the round robin protocol but lacks a decisive advantage over more advanced methods such as steepest descent or simulated annealing despite remaining competitive. The primary obstacle to scalability is found to be limited coupling on current quantum annealing hardware. However, for the more complex particle formulation, approached as a multiobjective optimization, quantum annealing solutions are demonstrably Pareto dominant to state of the art classical methods across both objectives. This signals a noteworthy advancement in solution quality which can have a large impact on effective CPU usage.

Citation

Rathore, O., Basden, A., Chancellor, N., & Kusumaatmaja, H. (2025). Load balancing for high performance computing using quantum annealing. Physical Review Research, 7(1), Article 013067. https://doi.org/10.1103/PhysRevResearch.7.013067

• Journal Article Type: Article
• Acceptance Date: Nov 9, 2024
• Online Publication Date: Jan 17, 2025
• Publication Date: 2025-03
• Deposit Date: Mar 5, 2025
• Publicly Available Date: Mar 5, 2025
• Journal: Physical Review Research
• Electronic ISSN: 2643-1564
• Publisher: American Physical Society
• Peer Reviewed: Peer Reviewed
• Volume: 7
• Issue: 1
• Article Number: 013067
• DOI: https://doi.org/10.1103/PhysRevResearch.7.013067
• Public URL: https://durham-repository.worktribe.com/output/3680480