Dynamic Solutions for Hybrid Quantum-HPC Resource Allocation
For researchers and engineers integrating quantum accelerators into HPC systems, this work addresses a practical resource management bottleneck, but the results are preliminary and lack quantitative validation.
The paper tackles resource allocation challenges in hybrid HPC-quantum systems by introducing malleability-based and workflow-based strategies that dynamically release and reallocate classical resources during quantum offloading. Experiments demonstrate improved resource utilization, though no concrete performance numbers are provided.
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.