High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System
We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approac...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2014/376456 |
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| author | Manob Jyoti Saikia Rajan Kanhirodan Ram Mohan Vasu |
| author_facet | Manob Jyoti Saikia Rajan Kanhirodan Ram Mohan Vasu |
| author_sort | Manob Jyoti Saikia |
| collection | DOAJ |
| description | We have developed a graphics processor unit (GPU-) based high-speed fully
3D system for diffuse optical tomography (DOT). The reduction in execution
time of 3D DOT algorithm, a severely
ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden
approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode
multithreaded GPU
and CUDA (Compute Unified Device Architecture) software
architecture.
Two different GPU implementations of DOT programs are developed in this study:
(1) conventional C language program augmented by GPU CUDA and CULA
routines (C GPU), (2)
MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU).
The computation time of the
algorithm on host CPU and the GPU system is presented for C and
Matlab implementations.
The forward computation uses finite element method (FEM) and
the problem domain is discretized into 14610, 30823, and 66514 tetrahedral
elements.
The reconstruction time, so achieved for one iteration of the DOT
reconstruction for 14610 elements, is
0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of
reconstructed frames so achieved is
2 frames per second. |
| format | Article |
| id | doaj-art-78b585f3ad9c418ebf6600cbd19df950 |
| institution | Kabale University |
| issn | 1687-4188 1687-4196 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Biomedical Imaging |
| spelling | doaj-art-78b585f3ad9c418ebf6600cbd19df9502025-02-03T01:21:58ZengWileyInternational Journal of Biomedical Imaging1687-41881687-41962014-01-01201410.1155/2014/376456376456High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic SystemManob Jyoti Saikia0Rajan Kanhirodan1Ram Mohan Vasu2Department of Physics, Indian Institute of Science, Bangalore 560012, IndiaDepartment of Physics, Indian Institute of Science, Bangalore 560012, IndiaDepartment of Instrumentation and Applied Physics, Indian Institute of Science, Bangalore 560012, IndiaWe have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode multithreaded GPU and CUDA (Compute Unified Device Architecture) software architecture. Two different GPU implementations of DOT programs are developed in this study: (1) conventional C language program augmented by GPU CUDA and CULA routines (C GPU), (2) MATLAB program supported by MATLAB parallel computing toolkit for GPU (MATLAB GPU). The computation time of the algorithm on host CPU and the GPU system is presented for C and Matlab implementations. The forward computation uses finite element method (FEM) and the problem domain is discretized into 14610, 30823, and 66514 tetrahedral elements. The reconstruction time, so achieved for one iteration of the DOT reconstruction for 14610 elements, is 0.52 seconds for a C based GPU program for 2-plane measurements. The corresponding MATLAB based GPU program took 0.86 seconds. The maximum number of reconstructed frames so achieved is 2 frames per second.http://dx.doi.org/10.1155/2014/376456 |
| spellingShingle | Manob Jyoti Saikia Rajan Kanhirodan Ram Mohan Vasu High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System International Journal of Biomedical Imaging |
| title | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
| title_full | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
| title_fullStr | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
| title_full_unstemmed | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
| title_short | High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System |
| title_sort | high speed gpu based fully three dimensional diffuse optical tomographic system |
| url | http://dx.doi.org/10.1155/2014/376456 |
| work_keys_str_mv | AT manobjyotisaikia highspeedgpubasedfullythreedimensionaldiffuseopticaltomographicsystem AT rajankanhirodan highspeedgpubasedfullythreedimensionaldiffuseopticaltomographicsystem AT rammohanvasu highspeedgpubasedfullythreedimensionaldiffuseopticaltomographicsystem |