Parallel Tensor Network Contraction for Efficient Quantum Circuit Simulation on Multicore CPUs and GPUs

Alfred M. Pastor, Maribel Castillo, Jose M. Badia

2025

Abstract

Quantum computing has the potential to transform fields such as cryptography, optimisation and materials science. However, the limited scalability and high error rates of current and near-term quantum hardware require efficient classical simulation of quantum circuits for validation and benchmarking. One of the most effective approaches to this problem is to represent quantum circuits as tensor networks, where simulation is equivalent to contracting the network. Given the computational cost of tensor network contraction, exploiting parallelism on modern high performance computing architectures is key to accelerating these simulations. In this work, we evaluate the performance of first-level parallelism in contracting individual tensor pairs during tensor network contraction on both multi-core CPUs and many-core GPUs. We compare the efficiency of three Julia packages, two optimised for CPU-based execution and the other for GPU acceleration. Our experiments, conducted with two parallel contraction strategies on highly entangled quantum circuits such as Quantum Fourier Transform (QFT) and Random Quantum Circuits (RQC), demonstrate the benefits of exploiting this level of parallelism on large circuits, in particular the superior performance gains achieved on GPUs.

Paper Citation

in Harvard Style

Pastor A., Castillo M. and Badia J. (2025). Parallel Tensor Network Contraction for Efficient Quantum Circuit Simulation on Multicore CPUs and GPUs. In Proceedings of the 1st International Conference on Quantum Software - Volume 1: IQSOFT; ISBN 978-989-758-761-0, SciTePress, pages 120-127. DOI: 10.5220/0013551400004525

in Bibtex Style

@conference{iqsoft25,
author={Alfred Pastor and Maribel Castillo and Jose Badia},
title={Parallel Tensor Network Contraction for Efficient Quantum Circuit Simulation on Multicore CPUs and GPUs},
booktitle={Proceedings of the 1st International Conference on Quantum Software - Volume 1: IQSOFT},
year={2025},
pages={120-127},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013551400004525},
isbn={978-989-758-761-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Quantum Software - Volume 1: IQSOFT
TI - Parallel Tensor Network Contraction for Efficient Quantum Circuit Simulation on Multicore CPUs and GPUs
SN - 978-989-758-761-0
AU - Pastor A.
AU - Castillo M.
AU - Badia J.
PY - 2025
SP - 120
EP - 127
DO - 10.5220/0013551400004525
PB - SciTePress