{
  "abstract": "The rapid development of Graphics Processing Units (GPUs) has established new computational paradigms for enhancing air quality modeling efficiency. In this study, the heterogeneous-compute interface for portability (HIP) was implemented to parallel computing of the piecewise parabolic method (PPM) advection solver (HADVPPM) on China's domestic GPU-like accelerators (GPU-like), resulting in a GPU-accelerated version denoted as GPU-HADVPPM4HIP V1.0. Computational performance was enhanced through three strategic optimizations: reducing the central processing unit (CPU) and GPU (CPU-GPU) data transfer frequency, thread-block coordinated indexing, and the Message Passing Interface (MPI) and HIP (“MPI+HIP”) hybrid parallelization across heterogeneous computing clusters. Following validation of the GPU-HADVPPM4HIP V1.0 program's offline computational consistency and the pollutant simulation performance of the Emission and atmospheric Processes Integrated and Coupled Community version 1.6.0 (EPICC-Model V1.6.0) on the Earth System Numerical Simulation Facility (EarthLab), comprehensive performance testing was conducted. Offline benchmark results demonstrated that, for a one-dimensional input array containing 10 ⁸ double-precision floating-point values, GPU-HADVPPM4HIP V1.0 compiled with the −O3 optimization option achieved a maximum speedup of 556.5× on a GPU-like accelerator relative to the Fortran HADVPPM implementation compiled with the −O0 option as the baseline. Integrating GPU-HADVPPM4HIP V1.0 into EPICC-Model V1.6.0 yielded three distinct versions: the initial HIP-based version (HIP-Ori), a version optimized for CPU and GPU communication frequency (HIP-Opt1), and a further-optimized version employing a thread-block coordinated indexing strategy (HIP-Opt2). Compared to the HIP-Ori version, HIP-Opt1 achieved a model-level computational efficiency improvement of 17.0×. Building upon HIP-Opt1, HIP-Opt2 delivered an additional 1.5× enhancement in computational efficiency. At the module level, including CPU and GPU data transfer overhead, the GPU implementation improves computational efficiency of the advection module by 39.3 %; when communication cost is excluded, the advection module attains a 20.5× acceleration relative to its CPU counterpart. This coupling establishes a foundational framework for adapting air quality models to GPU-like architectures and identifies critical optimization pathways. Moreover, the methodology provides essential technical support for achieving full-model GPU implementation of the EPICC-Model, addressing both current computational constraints and future demands for high-resolution air quality simulations.",
  "abstract_shown": true,
  "affiliations": [
    "Beijing Normal University (Beijing, China)",
    "Institute of Atmospheric Physics (Beijing, China)",
    "University of Chinese Academy of Sciences (Beijing, China)"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 12,
  "authors": [
    {
      "name": "Kai Cao"
    },
    {
      "affs": [
        0
      ],
      "name": "Qizhong Wu",
      "orcid": "0000-0001-6308-3083"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Xiao Tang"
    },
    {
      "name": "Jinxi Li"
    },
    {
      "name": "Xueshun Chen"
    },
    {
      "name": "Huansheng Chen"
    },
    {
      "name": "Wending Wang"
    },
    {
      "name": "Huangjian Wu"
    },
    {
      "name": "Lei Kong",
      "orcid": "0000-0003-1162-2158"
    },
    {
      "name": "Jie Li"
    },
    {
      "name": "Jiang Zhu"
    },
    {
      "name": "Zifa Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bpz33zvnvt7wt.bib",
  "cited_by": 0,
  "doi": "10.5194/gmd-19-9807-2026",
  "fulltext_url": null,
  "id": "bpz33zvnvt7wt",
  "issns": [
    "1991-9603"
  ],
  "landing_url": "https://gmd.copernicus.org/articles/19/9807/2026/",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1708|Parallel Computing and Optimization Techniques"
    ]
  ],
  "openalex": "W4414392340",
  "pdf_url": "https://gmd.copernicus.org/articles/19/9807/2026/gmd-19-9807-2026.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-13",
  "publisher": "Copernicus GmbH",
  "ris": "https://research.draconitic.com/paper/bpz33zvnvt7wt.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:49Z",
      "native_id": "10.5194/gmd-19-9807-2026",
      "source": "crossref",
      "url": "https://gmd.copernicus.org/articles/19/9807/2026/"
    }
  ],
  "subjects": [
    {
      "field": "earth",
      "origin": "issn:1991-9603",
      "subfield": "general"
    }
  ],
  "title": "Enhancing the advection module performance in the EPICC-Model V1.6.0 via GPU-HADVPPM4HIP V1.0 coupling and GPU-optimized strategies",
  "title_text": "Enhancing the advection module performance in the EPICC-Model V1.6.0 via GPU-HADVPPM4HIP V1.0 coupling and GPU-optimized strategies",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:49Z",
  "url": "https://research.draconitic.com/paper/bpz33zvnvt7wt",
  "venue": "Geoscientific Model Development",
  "versions": [
    {
      "doi": "10.5194/egusphere-2026-3368",
      "pid": null,
      "relation": "preprint",
      "title": null,
      "venue": null
    }
  ]
}