{
  "abstract": "Three-dimensional phase-field simulations are a gold-standard for microstructure prediction for materials, but their computational cost often limits application-relevant calculations to modest domain sizes and timescales. Here, we present a holistic approach for accelerating Fourier pseudospectral phase-field simulations by combining performance-portable GPU computing, large-scale distributed-memory parallelism, and high-order implicit-explicit time integration within the MEUMAPPS C++ framework. We demonstrate this approach with a 1.5-billion-grid-point simulation of the growth and coarsening of 1,920 gamma'' precipitates in a Ni-Nb-Fe alloy. The simulated seven-hour heat treatment is completed in 5.5 hours, making the calculation faster than real time and an estimated 217-501x faster than a CPU-only, first-order baseline. This performance makes three-dimensional simulations of thousands of interacting precipitates tractable, enabling quantitative studies ocollective microstructural phenomena, large simulation ensembles, and real-time integration into controlling and interpreting experiments. Benchmarking shows single-node GPU speedups of up to 17.5x relative to comparable CPU resources, near-ideal strong scaling to 4096 GPUs for a 12-billion-grid-point problem, and a further 2.6-2.9x acceleration from fourth-order time integration at scientifically relevant error tolerances. These results establish a performance-portable strategy for exploiting leadership-scale GPU systems that is applicable to a broad class of Fourier pseudospectral simulations beyond phase-field models such as fluid dynamics and crystal plasticity simulations.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.36100",
  "author_total": 7,
  "authors": [
    {
      "name": "Stephen DeWitt"
    },
    {
      "name": "David J. Gardner"
    },
    {
      "name": "Philip Fackler"
    },
    {
      "name": "Yonggil Song"
    },
    {
      "name": "Miroslav Stoyanov"
    },
    {
      "name": "Carol S. Woodward"
    },
    {
      "name": "Balasubramaniam Radhakrishnan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dqzna21dztdk2.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.36100",
  "fulltext_url": null,
  "id": "dqzna21dztdk2",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.36100",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cond-mat.mtrl-sci"
    ],
    [
      "openalex",
      "1708|Parallel Computing and Optimization Techniques"
    ]
  ],
  "openalex": "W7214993748",
  "pdf_url": "https://arxiv.org/pdf/2609.36100",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dqzna21dztdk2.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:31Z",
      "native_id": "2609.36100",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.36100"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.mtrl-sci",
      "subfield": "condensed-matter"
    }
  ],
  "title": "Accelerating phase-field simulations on exascale computing systems for faster-than-real-time precipitate aging predictions",
  "title_text": "Accelerating phase-field simulations on exascale computing systems for faster-than-real-time precipitate aging predictions",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:31Z",
  "url": "https://research.draconitic.com/paper/dqzna21dztdk2",
  "venue": "arXiv",
  "versions": []
}