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Study on efficiency of time computation in x-ray imaging simulation base on Monte Carlo algorithm using graphics processing unit

Journal Article · · AIP Conference Proceedings
DOI:https://doi.org/10.1063/1.4943702· OSTI ID:22590865
 [1];  [2]
  1. Computational Science, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung Jalan Ganesha 10 Bandung, 40132 (Indonesia)
  2. Nuclear Physics and Biophysics Reaserch Division, Faculty of Mathematics and Natural Sciences, Institut Teknologi Bandung Jalan Ganesha 10 Bandung, 40132 (Indonesia)

Monte Carlo (MC) is one of the powerful techniques for simulation in x-ray imaging. MC method can simulate the radiation transport within matter with high accuracy and provides a natural way to simulate radiation transport in complex systems. One of the codes based on MC algorithm that are widely used for radiographic images simulation is MC-GPU, a codes developed by Andrea Basal. This study was aimed to investigate the time computation of x-ray imaging simulation in GPU (Graphics Processing Unit) compared to a standard CPU (Central Processing Unit). Furthermore, the effect of physical parameters to the quality of radiographic images and the comparison of image quality resulted from simulation in the GPU and CPU are evaluated in this paper. The simulations were run in CPU which was simulated in serial condition, and in two GPU with 384 cores and 2304 cores. In simulation using GPU, each cores calculates one photon, so, a large number of photon were calculated simultaneously. Results show that the time simulations on GPU were significantly accelerated compared to CPU. The simulations on the 2304 core of GPU were performed about 64 -114 times faster than on CPU, while the simulation on the 384 core of GPU were performed about 20 – 31 times faster than in a single core of CPU. Another result shows that optimum quality of images from the simulation was gained at the history start from 10{sup 8} and the energy from 60 Kev to 90 Kev. Analyzed by statistical approach, the quality of GPU and CPU images are relatively the same.

OSTI ID:
22590865
Journal Information:
AIP Conference Proceedings, Journal Name: AIP Conference Proceedings Journal Issue: 1 Vol. 1719; ISSN APCPCS; ISSN 0094-243X
Country of Publication:
United States
Language:
English