PennyLane-Lightning MPI: A massively scalable quantum circuit simulator based on distributed computing in CPU clusters

TL;DR

This paper introduces PennyLane-Lightning MPI, a scalable quantum circuit simulator that leverages distributed computing in CPU clusters to simulate up to 41 qubits efficiently, facilitating quantum algorithm development and testing.

Contribution

It presents a novel MPI-based extension for PennyLane-Lightning that enables massively scalable quantum circuit simulations on distributed-memory systems.

Findings

Supports simulation of up to 41 qubits with hundreds of thousands of processes.

Offers performance advantages over traditional matrix-based methods.

Exhibits excellent scalability in distributed quantum circuit simulations.

Abstract

Quantum circuit simulations play a critical role in bridging the gap between theoretical quantum algorithms and their practical realization on physical quantum hardware, yet they face computational challenges due to the exponential growth of quantum state spaces with increasing qubit size. This work presents PennyLane-Lightning MPI, an MPI-based extension of the PennyLane-Lightning suite, developed to enable scalable quantum circuit simulations through parallelization of quantum state vectors and gate operations across distributed-memory systems. The core of this implementation is an index-dependent, gate-specific parallelization strategy, which fully exploits the characteristic of individual gates as well as the locality of computation associated with qubit indices in partitioned state vectors. Benchmarking tests with single gates and well-designed quantum circuits show that the present method offers advantages in performance over general methods based on unitary matrix operations and exhibits excellent scalability, supporting simulations of up to 41-qubit with hundreds of thousands of parallel processes. Being equipped with a Python plug-in for seamless integration to the PennyLane framework, this work contributes to extending the PennyLane ecosystem by enabling high-performance quantum simulations in standard multi-core CPU clusters with no library-specific requirements, providing a back-end resource for the cloud-based service framework of quantum computing that is under development in the Republic of Korea.