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<p><i>N</i>-body simulation serves as a critical method for modeling cosmic evolution and poses a significant challenge in high-performance computing. We present CUBE2, an open-source cosmological <i>N</i>-body code emphasizing memory efficiency, computational performance, scalability, and precision. The core of its algorithm utilizes a multi-level particle-mesh (PM) method to solve the Poisson equation for matter distribution, leveraging the well-optimized fast Fourier transform (FFT) for computational efficiency. Precision is ensured by the optimized Green’s function that seamlessly bridges gravitational interactions between multi-level PM and particle-particle (PP) calculations. The program design enhances per-core/node efficiency in processing <i>N</i>-body particles, while the information optimized storage (IOS) addresses memory constraints for large particle counts. Using CUBE2, we run two cosmological simulations with particle counts of 6144<sup>3</sup> on the Advanced Computing East China Sub-center (ACECS) to test performance and accuracy.</p>

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CUBE2: A parallel N-body simulation code for scalability, accuracy, and memory efficiency

  • 期刊论文

  • 发表日期：

    2026年2月28日

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  • Hao-Ran Yu,
  • Bing-Hang Chen,
  • Kun Xu,
  • Ming-Jie Sheng,
  • Jiaxin Han,
  • Yipeng Jing,
  • Huahua Cui

摘要

N-body simulation serves as a critical method for modeling cosmic evolution and poses a significant challenge in high-performance computing. We present CUBE2, an open-source cosmological N-body code emphasizing memory efficiency, computational performance, scalability, and precision. The core of its algorithm utilizes a multi-level particle-mesh (PM) method to solve the Poisson equation for matter distribution, leveraging the well-optimized fast Fourier transform (FFT) for computational efficiency. Precision is ensured by the optimized Green’s function that seamlessly bridges gravitational interactions between multi-level PM and particle-particle (PP) calculations. The program design enhances per-core/node efficiency in processing N-body particles, while the information optimized storage (IOS) addresses memory constraints for large particle counts. Using CUBE2, we run two cosmological simulations with particle counts of 61443 on the Advanced Computing East China Sub-center (ACECS) to test performance and accuracy.