Accelerating Monte Carlo simulations of photon transport in a voxelized geometry using a massively parallel graphics processing unit.
OBJECTIVE
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 CUDATM 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.
Badal
Andreu
A
Division of Imaging and Applied Mathematics, OSEL, CDRH, U.S. Food and Drug Administration, Silver Spring, Maryland 20993-0002, USA. andreu.badal-soler@fda.hhs.gov
Badano
Aldo
A
D000465:Algorithms; D003198:Computer Simulation; D003201:Computers; D004581:Electronics / Q000295:instrumentation*; D006801:Humans; D008953:Models, Anatomic; D009010:Monte Carlo Method; D019047:Phantoms, Imaging; D017785:Photons; D012542:Scattering, Radiation; D012984:Software; D013997:Time Factors; D014965:X-Rays