Literature DB >> 26061350

A study of potential numerical pitfalls in GPU-based Monte Carlo dose calculation.

Vincent Magnoux1, Benoît Ozell, Éric Bonenfant, Philippe Després.   

Abstract

The purpose of this study was to evaluate the impact of numerical errors caused by the floating point representation of real numbers in a GPU-based Monte Carlo code used for dose calculation in radiation oncology, and to identify situations where this type of error arises. The program used as a benchmark was bGPUMCD. Three tests were performed on the code, which was divided into three functional components: energy accumulation, particle tracking and physical interactions. First, the impact of single-precision calculations was assessed for each functional component. Second, a GPU-specific compilation option that reduces execution time as well as precision was examined. Third, a specific function used for tracking and potentially more sensitive to precision errors was tested by comparing it to a very high-precision implementation. Numerical errors were found in two components of the program. Because of the energy accumulation process, a few voxels surrounding a radiation source end up with a lower computed dose than they should. The tracking system contained a series of operations that abnormally amplify rounding errors in some situations. This resulted in some rare instances (less than 0.1%) of computed distances that are exceedingly far from what they should have been. Most errors detected had no significant effects on the result of a simulation due to its random nature, either because they cancel each other out or because they only affect a small fraction of particles. The results of this work can be extended to other types of GPU-based programs and be used as guidelines to avoid numerical errors on the GPU computing platform.

Mesh:

Year:  2015        PMID: 26061350     DOI: 10.1088/0031-9155/60/13/5007

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  3 in total

1.  Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy.

Authors:  Nan Qin; Marco Pinto; Zhen Tian; Georgios Dedes; Arnold Pompos; Steve B Jiang; Katia Parodi; Xun Jia
Journal:  Phys Med Biol       Date:  2017-01-31       Impact factor: 3.609

2.  Recent developments and comprehensive evaluations of a GPU-based Monte Carlo package for proton therapy.

Authors:  Nan Qin; Pablo Botas; Drosoula Giantsoudi; Jan Schuemann; Zhen Tian; Steve B Jiang; Harald Paganetti; Xun Jia
Journal:  Phys Med Biol       Date:  2016-10-03       Impact factor: 3.609

3.  A Novel GPU-based Fast Monte Carlo Photon Dose Calculating Method for Accurate Radiotherapy Treatment Planning.

Authors:  Karbalaee M; Shahbazi-Gahrouei D; Tavakoli M B
Journal:  J Biomed Phys Eng       Date:  2020-06-01
  3 in total

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