2019/07/25 by Fang Zhang, Cupjin Huang, Zhang, Fang +23
Computer Science · #Cloud Computing and Resource Management #FOS: Physical sciences #Quantum Computing Algorithms and Architecture #Quantum Physics (quant-ph)
paper · pdf · doi:10.48550/arxiv.1907.11217
openalex publication_date 2019/07/25 · openalex created_date 2024/04/11 · openalex updated_date 2026/07/28
We report, in a sequence of notes, our work on the Alibaba Cloud Quantum Development Platform(AC-QDP). AC-QDP provides a set of tools for aiding the development of both quantum computing algorithms and quantum processors, and is powered by a large-scale classical simulator deployed on Alibaba Cloud. In this note, we report the computational experiments demonstrating the classical simulation capability of AC-QDP. We use as a benchmark the random quantum circuits designed for Google's Bristlecone QPU \citeGRCS. We simulate Bristlecone-70 circuits with depth 1 + 32 + 1 in 0.43 second per amplitude, using 1449 Alibaba Cloud Elastic Computing Service (ECS) instances, each with 88 Intel Xeon(Skylake) Platinum 8163 vCPU cores @ 2.5 GHz and 160 gigabytes of memory. By comparison, the previously best reported results for the same tasks are 104 and 135 seconds, using NASA's HPC Pleiades and Electra systems, respectively (arXiv:1811.09599). Furthermore, we report simulations of Bristlecone-70 with depth 1+36+1 and depth 1+40+1 in 5.6 and 580.7 seconds per amplitude, respectively. To the best of our knowledge, these are the first successful simulations of instances at these depths.