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Area of Science:

  • Medical Physics
  • Computational Science
  • Particle Physics

Background:

  • Graphics-processing unit (GPU) platforms offer significant speedups for Monte Carlo (MC) particle transport simulations via massive parallelization.
  • Existing GPU-based MC packages are primarily limited to voxelized geometries, restricting their applicability.
  • There is a need for MC simulation tools that can handle more complex, non-voxelized geometries on GPUs.

Purpose of the Study:

  • To develop and integrate a module for modeling parametric geometry within GPU-based MC simulations.
  • To enable MC simulations of particle transport in complex, continuous geometries beyond voxelized representations.
  • To evaluate the accuracy and efficiency of the developed parametric geometry module.

Main Methods:

  • Developed a module defining continuous regions by bounding surfaces parameterized by quadratic functions.
  • Implemented particle navigation functions for the parametric geometry.
  • Integrated the module into existing GPU-based MC packages.
  • Tested simulations for low energy photon transport (brachytherapy) and MeV coupled photon/electron transport in phantoms with various inserts.
  • Investigated the impact of data storage (GPU shared memory) and an auxiliary index array on computational speed.

Main Results:

  • Calculated dose distributions in parametric geometry showed excellent agreement with voxelized geometry counterparts (averaged dose differences of 1.03% and 0.29%).
  • Simulations of a Varian VS 2000 brachytherapy source were performed, generating a phase-space file.
  • Highest computational speed was achieved when geometry data was stored in GPU's shared memory.
  • Parametric geometry incorporation was ~3 times slower than voxelized geometry initially, but an auxiliary index array strategy reduced this to 1.75-2.03 times for coupled transport and 0.69-1.23 times for photon-only transport.

Conclusions:

  • The developed parametric geometry module effectively extends GPU-based MC simulations to handle complex shapes.
  • The module provides accurate dose calculations comparable to voxelized methods.
  • Optimization strategies, including data storage and auxiliary indexing, are crucial for improving computational efficiency in parametric GPU MC simulations.