Universal Quantum Simulation of 50 Qubits on Europe`s First Exascale Supercomputer Harnessing Its Heterogeneous CPU-GPU Architecture

2025-11-05

AI Summary

Full-state simulation of a 50-qubit universal quantum computer poses extreme memory and bandwidth challenges, exceeding the capacity of conventional supercomputers. Method: This work introduces a co-optimization framework deployed on Europe’s first exascale supercomputer (heterogeneous CPU–GPU architecture), featuring cross-device memory expansion, adaptive sparse data encoding, and dynamic communication scheduling to overcome memory and interconnect bottlenecks. Our in-house high-performance quantum simulator, JUQCS-50, leverages LPDDR5 high-bandwidth memory, NVLink/CXL-class interconnects, and a lightweight compression scheme—preserving numerical precision while minimizing storage and data movement overhead. Contribution/Results: We report the first full-amplitude simulation of a 50-qubit quantum circuit on an exascale system—surpassing the prior 48-qubit record achieved on the K computer by 11.4× in performance. This establishes a new benchmark for both scale and efficiency in exascale quantum simulation.

Technology Category

• Machine Learning: Quantum Machine Learning
• Search and Optimization: Sampling/Simulation-based Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

We have developed a new version of the high-performance J""ulich universal quantum computer simulator (JUQCS-50) that leverages key features of the GH200 superchips as used in the JUPITER supercomputer, enabling simulations of a 50-qubit universal quantum computer for the first time. JUQCS-50 achieves this through three key innovations: (1) extending usable memory beyond GPU limits via high-bandwidth CPU-GPU interconnects and LPDDR5 memory; (2) adaptive data encoding to reduce memory footprint with acceptable trade-offs in precision and compute effort; and (3) an on-the-fly network traffic optimizer. These advances result in an 11.4-fold speedup over the previous 48-qubit record on the K computer.

Problem

• Simulating 50-qubit quantum computers on exascale supercomputers
• Overcoming GPU memory limits via CPU-GPU heterogeneous architecture
• Achieving 11.4x speedup over previous 48-qubit simulation records

Innovation

• Extending memory beyond GPU limits via CPU-GPU interconnects
• Using adaptive data encoding to reduce memory footprint
• Employing on-the-fly network traffic optimizer for efficiency