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<p>The Fire Dynamics Simulator (FDS) is widely used for fire simulation but faces scalability challenges due to its limited grid partitioning capabilities. To address this issue, we propose Para-FDS, a scalable multilevel parallel scheme for accelerating FDS targeted at multicore architectures. Para-FDS integrates three key optimizations: (1) an adaptive grid partitioning algorithm to enhance scalability, (2) a communication localization optimization approach to reduce overhead between computing nodes, and (3) a NUMA-aware process mapping strategy to improve core utilization within Non-Uniform Memory Access (NUMA) architecture. Implemented on the Tianhe next-generation supercomputer, Para-FDS achieves a speedup of up to <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(214\times\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mn>214</mn> <mo>×</mo> </mrow> </math></EquationSource> </InlineEquation> on a practical example. It further reduces communication overhead by up to 38% and execution time by up to 22%, significantly improving FDS scalability and efficiency.</p>

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Para-FDS: a scalable multilevel parallel scheme for fire dynamic simulator on multicore architectures

  • 期刊论文

  • 发表日期：

    2025年11月5日

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  • Dazheng Liu,
  • Sheng Xiao,
  • Xiaoli Ren,
  • Wenjuan Liu,
  • Dajiang Yi,
  • Zean Tian,
  • Jianping Wu,
  • Yongan Wu,
  • Zuodong Niu,
  • Keqin Li,
  • Shaoliang Peng

摘要

The Fire Dynamics Simulator (FDS) is widely used for fire simulation but faces scalability challenges due to its limited grid partitioning capabilities. To address this issue, we propose Para-FDS, a scalable multilevel parallel scheme for accelerating FDS targeted at multicore architectures. Para-FDS integrates three key optimizations: (1) an adaptive grid partitioning algorithm to enhance scalability, (2) a communication localization optimization approach to reduce overhead between computing nodes, and (3) a NUMA-aware process mapping strategy to improve core utilization within Non-Uniform Memory Access (NUMA) architecture. Implemented on the Tianhe next-generation supercomputer, Para-FDS achieves a speedup of up to \(214\times\) 214 × on a practical example. It further reduces communication overhead by up to 38% and execution time by up to 22%, significantly improving FDS scalability and efficiency.