QPanda3: A High-Performance Software-Hardware Collaborative Framework for Large-Scale Quantum-Classical Computing Integration
April 03, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Tianrui Zou, Yuan Fang, Jing Wang, Menghan Dou, Jun Fu, ZiQiang Zhao, ShuBin Zhao, Lei Yu, Dongyi Zhao, Zhaoyun Chen, Guoping Guo
arXiv ID
2504.02455
Category
cs.PL: Programming Languages
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
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.
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