2025/04/26 by Fuad Hasan, Cameron Smith, Hasan, Fuad +12 · 1 citation
Engineering · Medicine · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Distributed #FOS: Computer and information sciences #FOS: Physical sciences #Magnetic confinement fusion research #Nuclear reactor physics and engineering #Parallel #Radiation Therapy and Dosimetry #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2504.19048
openalex publication_date 2025/04/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Unstructured mesh tallies are a bottleneck in Monte Carlo neutral particle transport simulations of fusion reactors. This paper introduces the PUMI-Tally library that takes advantage of mesh adjacency information to accelerate these tallies on CPUs and GPUs. For a fixed source simulation using track-length tallies, we achieved a speed-up of 19.7X on an NVIDIA A100, and 9.2X using OpenMP on 128 threads of two AMD EPYC 7763 CPUs on NERSC Perlmutter. On the Empire AI alpha system, we achieved a speed-up of 20X using an NVIDIA H100 and 96 threads of an Intel Xenon 8568Y+. Our method showed better scaling with number of particles and number of elements. Additionally, we observed a 199X reduction in the number of allocations during initialization and the first three iterations, with a similar overall memory consumption. And, our hybrid CPU/GPU method demonstrated a 6.69X improvement in the energy consumption over the current approach.