This work addresses the growing computational demands of quantum circuit simulation in the Noisy Intermediate-Scale Quantum (NISQ) era, where limited qubit counts, noise, and shallow circuit depths constrain practical quantum hardware.
Classical simulators remain essential for advancing quantum algorithm research, enabling validation, benchmarking, and exploration of hardware limitations across diverse computing platforms.
Among them, the Quantum Exact Simulation Toolkit (QuEST) provides a high-performance, scalable solution supporting state vector and density matrix simulations across distributed, shared-memory, and GPU-accelerated systems.
However, large-scale simulations on shared high-performance computing (HPC) infrastructures often suffer from resource contention and inefficient utilization.
To address this, we investigate the integration of QuEST with the Dynamic Management of Resources (DMR) framework, enabling malleability for MPI-based applications.
This approach allows simulations to dynamically adapt their resource footprint at runtime, improving system responsiveness and efficiency.
We present a case study demonstrating the benefits of this integration, showing that malleable quantum simulations can reduce wait times, enhance resource utilization, and improve scalability.
Our results highlight the potential of combining high-performance quantum simulation with dynamic resource management to better exploit modern HPC environments.
