A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues

A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues

Monte Carlo simulation is a precise method to model light propagation in bio-tissues and has been considered the golden standard to estimate the result of other computation methods. But the huge computation burden limited the application. In this paper, we propose a parallel computing model using gr...

Full description

Bibliographic Details
Main Authors: Xiang Fang, Hao Li, Weichao Liu, Yingxin Li, Ting Li
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Bio-tissue
graphic card acceleration
light propagation
Monte Carlo simulation
parallel mode
Online Access:https://ieeexplore.ieee.org/document/8737677/
id doaj-05acca05e6c1433b85d70d3a566e1432
record_format Article
spelling doaj-05acca05e6c1433b85d70d3a566e14322021-03-30T00:12:12ZengIEEEIEEE Access2169-35362019-01-017815938159810.1109/ACCESS.2019.29233208737677A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-TissuesXiang Fang0Hao Li1Weichao Liu2Yingxin Li3Ting Li4https://orcid.org/0000-0001-5145-3024Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, ChinaBeijing Key Laboratory of Digital Media, School of Computer Science and Engineering, Beihang University, Beijing, ChinaInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, ChinaInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, ChinaInstitute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, ChinaMonte Carlo simulation is a precise method to model light propagation in bio-tissues and has been considered the golden standard to estimate the result of other computation methods. But the huge computation burden limited the application. In this paper, we propose a parallel computing model using graphic card to accelerate the Monte Carlo simulation in 3-D voxelized media with the consideration of internal refraction. Optimization of the parallel mode is made by using segmentations and offered an extra boost of simulation speed. The acceleration efficiency affecting factors are investigated and the acceleration rate of the five segmented model is 32.6 times higher than non-GPU model and 1.66 times higher than non-optimized model for a real human head 3-D structure simulation.https://ieeexplore.ieee.org/document/8737677/Bio-tissuegraphic card accelerationlight propagationMonte Carlo simulationparallel mode
collection DOAJ
language English
format Article
sources DOAJ
author Xiang Fang
Hao Li
Weichao Liu
Yingxin Li
Ting Li
spellingShingle Xiang Fang
Hao Li
Weichao Liu
Yingxin Li
Ting Li
A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues
IEEE Access
Bio-tissue
graphic card acceleration
light propagation
Monte Carlo simulation
parallel mode
author_facet Xiang Fang
Hao Li
Weichao Liu
Yingxin Li
Ting Li
author_sort Xiang Fang
title A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues
title_short A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues
title_full A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues
title_fullStr A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues
title_full_unstemmed A Parallel Mode Optimized GPU Accelerated Monte Carlo Model for Light Propagation in 3-D Voxelized Bio-Tissues
title_sort parallel mode optimized gpu accelerated monte carlo model for light propagation in 3-d voxelized bio-tissues
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2019-01-01
description Monte Carlo simulation is a precise method to model light propagation in bio-tissues and has been considered the golden standard to estimate the result of other computation methods. But the huge computation burden limited the application. In this paper, we propose a parallel computing model using graphic card to accelerate the Monte Carlo simulation in 3-D voxelized media with the consideration of internal refraction. Optimization of the parallel mode is made by using segmentations and offered an extra boost of simulation speed. The acceleration efficiency affecting factors are investigated and the acceleration rate of the five segmented model is 32.6 times higher than non-GPU model and 1.66 times higher than non-optimized model for a real human head 3-D structure simulation.
topic Bio-tissue
graphic card acceleration
light propagation
Monte Carlo simulation
parallel mode
url https://ieeexplore.ieee.org/document/8737677/
work_keys_str_mv AT xiangfang aparallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT haoli aparallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT weichaoliu aparallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT yingxinli aparallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT tingli aparallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT xiangfang parallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT haoli parallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT weichaoliu parallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT yingxinli parallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
AT tingli parallelmodeoptimizedgpuacceleratedmontecarlomodelforlightpropagationin3dvoxelizedbiotissues
_version_ 1724188510312726528

Similar Items