QPanda3: A High-Performance Software-Hardware Collaborative Framework for Large-Scale Quantum-Classical Computing Integration

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Zou, Tianrui, Fang, Yuan, Wang, Jing, Dou, Menghan, Fu, Jun, Zhao, ZiQiang, Zhao, ShuBin, Yu, Lei, Zhao, Dongyi, Chen, Zhaoyun, Guo, Guoping
Formato: Preprint
Publicado: 2025
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866909648132505600
author Zou, Tianrui
Fang, Yuan
Wang, Jing
Dou, Menghan
Fu, Jun
Zhao, ZiQiang
Zhao, ShuBin
Yu, Lei
Zhao, Dongyi
Chen, Zhaoyun
Guo, Guoping
author_facet Zou, Tianrui
Fang, Yuan
Wang, Jing
Dou, Menghan
Fu, Jun
Zhao, ZiQiang
Zhao, ShuBin
Yu, Lei
Zhao, Dongyi
Chen, Zhaoyun
Guo, Guoping
contents In emerging quantum-classical integration applications, the classical time cost-especially from compilation and protocol-level communication often exceeds the execution time of quantum circuits themselves, posing a severe bottleneck to practical deployment. To overcome these limitations, QPanda3 has been extensively optimized as a high-performance quantum programming framework tailored for the demands of the NISQ era and quantum-classical hybrid workflows. It features optimized circuit compilation, a custom binary instruction stream (OriginBIS), and hardware-aware execution strategies to significantly reduce latency and communication overhead. OriginBIS achieves up to 86.9$\times$ faster encoding and 35.6$\times$ faster decoding than OpenQASM 2.0, addressing critical bottlenecks in hybrid quantum systems. Benchmarks show 10.7$\times$ compilation speedup and up to 597$\times$ acceleration in compiling large-scale circuits (e.g., a 118-qubit W-state) compared to Qiskit. n high-performance simulation, QPanda3 excels in variational quantum algorithms, achieving up to 26$\times$ faster gradient computation than Qiskit, with minimal time-complexity growth across circuit depths. These capabilities make QPanda3 well-suited for scalable quantum algorithm development in finance, materials science, and combinatorial optimization, while supporting industrial deployment and cloud-based execution in quantum-classical hybrid computing scenarios.
format Preprint
id arxiv_https___arxiv_org_abs_2504_02455
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle QPanda3: A High-Performance Software-Hardware Collaborative Framework for Large-Scale Quantum-Classical Computing Integration
Zou, Tianrui
Fang, Yuan
Wang, Jing
Dou, Menghan
Fu, Jun
Zhao, ZiQiang
Zhao, ShuBin
Yu, Lei
Zhao, Dongyi
Chen, Zhaoyun
Guo, Guoping
Programming Languages
In emerging quantum-classical integration applications, the classical time cost-especially from compilation and protocol-level communication often exceeds the execution time of quantum circuits themselves, posing a severe bottleneck to practical deployment. To overcome these limitations, QPanda3 has been extensively optimized as a high-performance quantum programming framework tailored for the demands of the NISQ era and quantum-classical hybrid workflows. It features optimized circuit compilation, a custom binary instruction stream (OriginBIS), and hardware-aware execution strategies to significantly reduce latency and communication overhead. OriginBIS achieves up to 86.9$\times$ faster encoding and 35.6$\times$ faster decoding than OpenQASM 2.0, addressing critical bottlenecks in hybrid quantum systems. Benchmarks show 10.7$\times$ compilation speedup and up to 597$\times$ acceleration in compiling large-scale circuits (e.g., a 118-qubit W-state) compared to Qiskit. n high-performance simulation, QPanda3 excels in variational quantum algorithms, achieving up to 26$\times$ faster gradient computation than Qiskit, with minimal time-complexity growth across circuit depths. These capabilities make QPanda3 well-suited for scalable quantum algorithm development in finance, materials science, and combinatorial optimization, while supporting industrial deployment and cloud-based execution in quantum-classical hybrid computing scenarios.
title QPanda3: A High-Performance Software-Hardware Collaborative Framework for Large-Scale Quantum-Classical Computing Integration
topic Programming Languages
url https://arxiv.org/abs/2504.02455