Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction
Abstract
We introduce a new open-source software library Jet, which uses task-based parallelism to obtain speed-ups in classical tensor-network simulations of quantum circuits. These speed-ups result from i) the increased parallelism introduced by mapping the tensor-network simulation to a task-based framework, ii) a novel method of reusing shared work between tensor-network contraction tasks, and iii) the concurrent contraction of tensor networks on all available hardware. We demonstrate the advantages of our method by benchmarking our code on several Sycamore-53 and Gaussian boson sampling (GBS) supremacy circuits against other simulators. We also provide and compare theoretical performance estimates for tensor-network simulations of Sycamore-53 and GBS supremacy circuits for the first time.
Cite
@article{arxiv.2107.09793,
title = {Jet: Fast quantum circuit simulations with parallel task-based tensor-network contraction},
author = {Trevor Vincent and Lee J. O'Riordan and Mikhail Andrenkov and Jack Brown and Nathan Killoran and Haoyu Qi and Ish Dhand},
journal= {arXiv preprint arXiv:2107.09793},
year = {2022}
}
Comments
Code: https://github.com/XanaduAI/jet