Quantum circuit simulations scale computing resources dynamically
Enabling Dynamic Resource Scaling in Quantum Circuit Simulations
Distributed, Parallel, and Cluster Computing
Summary
Simulating quantum circuits with different numbers of qubits is tricky because more qubits need more computing power. The authors made a tool that can change the amount of computing resources it uses between simulations automatically. This means running several quantum circuits of varying sizes in one job without wasting any computers or waiting in queues. They showed this works well on a real supercomputer with almost no delay.
What this means in practice
- •For high-performance computing operators: Run quantum circuit simulations of varying sizes in one computing job, reducing idle resources and overhead from multiple job submissions.
- •For cloud infrastructure teams: Support dynamic resizing of computational resources for workloads where problem sizes change unpredictably, improving efficiency and throughput.
Authors
Íñigo Aréjula-Aísa, Sergio Iserte, Petter Sandås, Ricard S. Raigada-García, Oliver Brown, James Richings, Antonio J. Peña
Abstract
Studies of quantum algorithms often simulate se- quences of circuits whose number of qubits changes from one circuit to the next, such as instances of increasing size of the same problem. Since each additional qubit doubles the state- vector, every circuit needs a different number of nodes, which a fixed allocation on a shared High-Performance Computing (HPC) system cannot provide: a job sized for the largest circuit leaves most of its nodes idle, and one job per circuit adds scheduler interactions and queue waits. We make the QuEST state-vector simulator malleable with the Dynamic Management of Resources (DMR) framework, so that a single job resizes between circuits. Because no state-vector exists between circuits, reconfigurations require no data redistribution and no changes to the simulation kernels, and a checkpoint holding the index of the next circuit is enough to resume. A right-sizing policy derives the number of nodes from the number of qubits, and the circuit_executor API hides reconfigurations from the user. We evaluate the reconfiguration overhead on MareNostrum 5 and show that a single job can run a batch of circuits of different sizes, adapting its allocation to each of them with negligible overhead.