ScaleQsim: Highly Scalable Quantum Circuit Simulation Framework for Exascale HPC Systems

Large-scale quantum circuit simulation on high-performance computing (HPC) systems is crucial for developing and verifying quantum algorithms to overcome the limitations of current noisy quantum computers. However, existing simulators face scalability bottlenecks due to memory limits and communication overhead. Many state-of-the-art approaches rely on static circuit partitioning, which makes it difficult to address the exponential growth in problem size as the number of qubits increases. To overcome these challenges, we present ScaleQsim, a highly scalable quantum circuit simulation framework for large-scale HPC systems. ScaleQsim focuses on providing a unified representation of the full qubit state, yet provides scalability through efficient synchronization and communication. ScaleQsim adopts a novel full state vector partitioning strategy that evenly distributes the full state vector across multiple nodes and GPUs. This distributed structure enables efficient parallel gate execution without costly synchronization, and ScaleQsim applies adaptive kernel configuration, which adjusts execution parameters based on GPU resources and task granularity to enhance simulation efficiency. Our evaluation on a leadership-scale supercomputer with up to 512 GPUs demonstrates that ScaleQsim simulates quantum circuits with up to 42 qubits and outperforms leading SOTA simulators by up to 77.40× across various quantum circuits.

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Publication Details

Journal
Proceedings of the ACM on Measurement and Analysis of Computing Systems
Published
2025-12-01
DOI
https://doi.org/10.1145/3771577
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

ScaleQsim: Highly Scalable Quantum Circuit Simulation Framework for Exascale HPC Systems

Changjong Kim, Seunghwan Kim, Houjun Tang, Kesheng Wu et al.
Proceedings of the ACM on Measurement and Analysis of Computing Systems
Quantum Computing Algorithms and Architecture
article

ScaleQsim: Highly Scalable Quantum Circuit Simulation Framework for Exascale HPC Systems

Changjong Kim, Seunghwan Kim, Houjun Tang, Kesheng Wu, Alex Sim, Yongseok Son, Sunggon Kim, Ehan Sohn
article en

Abstract

Large-scale quantum circuit simulation on high-performance computing (HPC) systems is crucial for developing and verifying quantum algorithms to overcome the limitations of current noisy quantum computers. However, existing simulators face scalability bottlenecks due to memory limits and communication overhead. Many state-of-the-art approaches rely on static circuit partitioning, which makes it difficult to address the exponential growth in problem size as the number of qubits increases. To overcome these challenges, we present ScaleQsim, a highly scalable quantum circuit simulation framework for large-scale HPC systems. ScaleQsim focuses on providing a unified representation of the full qubit state, yet provides scalability through efficient synchronization and communication. ScaleQsim adopts a novel full state vector partitioning strategy that evenly distributes the full state vector across multiple nodes and GPUs. This distributed structure enables efficient parallel gate execution without costly synchronization, and ScaleQsim applies adaptive kernel configuration, which adjusts execution parameters based on GPU resources and task granularity to enhance simulation efficiency. Our evaluation on a leadership-scale supercomputer with up to 512 GPUs demonstrates that ScaleQsim simulates quantum circuits with up to 42 qubits and outperforms leading SOTA simulators by up to 77.40× across various quantum circuits.

Proceedings of the ACM on Measurement and Analysis of Computing SystemsVol. 9(3)
Seoul National University of Science and Technology (KR), Lawrence Berkeley National Laboratory (US), Chung-Ang University (KR)
Openalex Percentile: Top 80%
Quantum Computing Algorithms and Architecture
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