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Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit
Author(s) -
Badal Andreu,
Badano Aldo
Publication year - 2009
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.3231824
Subject(s) - monte carlo method , cuda , graphics processing unit , computer science , computational science , imaging phantom , graphics , parallel computing , massively parallel , acceleration , computer graphics (images) , physics , optics , mathematics , statistics , classical mechanics
Purpose: It is a known fact that Monte Carlo simulations of radiation transport are computationally intensive and may require long computing times. The authors introduce a new paradigm for the acceleration of Monte Carlo simulations: The use of a graphics processing unit (GPU) as the main computing device instead of a central processing unit (CPU). Methods: A GPU‐based Monte Carlo code that simulates photon transport in a voxelized geometry with the accurate physics models from PENELOPE has been developed using the CUDA ™ programming model (NVIDIA Corporation, Santa Clara, CA). Results: An outline of the new code and a sample x‐ray imaging simulation with an anthropomorphic phantom are presented. A remarkable 27‐fold speed up factor was obtained using a GPU compared to a single core CPU. Conclusions: The reported results show that GPUs are currently a good alternative to CPUs for the simulation of radiation transport. Since the performance of GPUs is currently increasing at a faster pace than that of CPUs, the advantages of GPU‐based software are likely to be more pronounced in the future.