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Hardware Acceleration of Biophotonic...

Young-Schultz, Tanner.

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Hardware Acceleration of Biophotonic Simulations.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Hardware Acceleration of Biophotonic Simulations./
Author:	Young-Schultz, Tanner.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	76 p.
Notes:	Source: Masters Abstracts International, Volume: 82-06.
Contained By:	Masters Abstracts International82-06.
Subject:	Computer engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28093078
ISBN:	9798698547815

Hardware Acceleration of Biophotonic Simulations.
Young-Schultz, Tanner.

Hardware Acceleration of Biophotonic Simulations. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 76 p.

Source: Masters Abstracts International, Volume: 82-06.

Thesis (M.A.S.)--University of Toronto (Canada), 2020.

This item must not be sold to any third party vendors.

The simulation of light propagation through tissue is important for medical applications like diffuse optical tomography (DOT), bioluminescence imaging (BLI) and photodynamic therapy (PDT). These applications involve solving an inverse problem, which works backwards from a light distribution to the parameters that caused it. These inverse problems have no general closed-form solution and therefore are approximated using iterative techniques. Increasing the accuracy of the approximation requires performing many light propagation simulations which is time-consuming and computationally intensive.We describe algorithmic techniques to improve the performance, accuracy and usability of the fastest software simulator for forward light propagation, FullMonteSW. Additionally, we explore two acceleration methods using a GPU and an FPGA. Our results show that the GPU and FPGA accelerator improve the performance by 4-13x and 4x, respectively, over the software baseline. We give insight for improving the performance and usability of the GPU- and FPGA-accelerated simulators for various medical applications.

ISBN: 9798698547815Subjects--Topical Terms:

621879
Computer engineering.
Subjects--Index Terms:

FPGA

Hardware Acceleration of Biophotonic Simulations.
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245 1 0 $a Hardware Acceleration of Biophotonic Simulations.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2020
300 $a 76 p.
500 $a Source: Masters Abstracts International, Volume: 82-06.
500 $a Advisor: Betz, Vaughn;Brown, Stephen.
502 $a Thesis (M.A.S.)--University of Toronto (Canada), 2020.
506 $a This item must not be sold to any third party vendors.
520 $a The simulation of light propagation through tissue is important for medical applications like diffuse optical tomography (DOT), bioluminescence imaging (BLI) and photodynamic therapy (PDT). These applications involve solving an inverse problem, which works backwards from a light distribution to the parameters that caused it. These inverse problems have no general closed-form solution and therefore are approximated using iterative techniques. Increasing the accuracy of the approximation requires performing many light propagation simulations which is time-consuming and computationally intensive.We describe algorithmic techniques to improve the performance, accuracy and usability of the fastest software simulator for forward light propagation, FullMonteSW. Additionally, we explore two acceleration methods using a GPU and an FPGA. Our results show that the GPU and FPGA accelerator improve the performance by 4-13x and 4x, respectively, over the software baseline. We give insight for improving the performance and usability of the GPU- and FPGA-accelerated simulators for various medical applications.
590 $a School code: 0779.
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650 4 $a Biomedical engineering. $3 535387
650 4 $a Histology. $3 641250
650 4 $a Medical imaging. $3 3172799
650 4 $a Information technology. $3 532993
650 4 $a Optics. $3 517925
653 $a FPGA
653 $a HPC
653 $a Monte Carlo
653 $a OpenCL
653 $a Biophonic simulations
653 $a Hardware acceleration
653 $a Software simulator
653 $a Light propagation
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690 $a 0752
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710 2 $a University of Toronto (Canada). $b Electrical and Computer Engineering. $3 2096349
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792 $a 2020
793 $a English
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