Electrical Impedance Tomography Methods and Algorithms Processed with a GPU

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F17%3APU124120" target="_blank" >RIV/00216305:26220/17:PU124120 - isvavai.cz</a>

Výsledek na webu

<a href="https://ieeexplore.ieee.org/document/8262025" target="_blank" >https://ieeexplore.ieee.org/document/8262025</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/PIERS.2017.8262025" target="_blank" >10.1109/PIERS.2017.8262025</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Electrical Impedance Tomography Methods and Algorithms Processed with a GPU

Popis výsledku v původním jazyce

The present paper discusses the process of parallelizing an algorithm for the reconstruction of an image acquired via electrical impedance tomography (EIT). The introductory section comprises a general description of EIT, the inverse problem, and regularization; in this context, the potential of the method for biomedicine, defectoscopy, and geophysical mapping is outlined. The following chapter then analyzes the objective function of the EIT inverse problem together with Tikhonov regularization. Besides setting up the objective function with a regularizing member, the authors also specify the differentiation equation for the iterative solution of the inverse problem via the Gauss-Newton method. Further, the time consumption of computing the Jacobian via a CPU compared to using a newly assembled program that exploits GPU-based parallel processing is investigated in detail. The program, utilizing the NVIDIA CUDA platform, employs parallelized computation of the individual columns of the Jacobi matrix, and this approach proved to be twenty times faster than the CPU-based sequential processing.

Název v anglickém jazyce

Electrical Impedance Tomography Methods and Algorithms Processed with a GPU

Popis výsledku anglicky

The present paper discusses the process of parallelizing an algorithm for the reconstruction of an image acquired via electrical impedance tomography (EIT). The introductory section comprises a general description of EIT, the inverse problem, and regularization; in this context, the potential of the method for biomedicine, defectoscopy, and geophysical mapping is outlined. The following chapter then analyzes the objective function of the EIT inverse problem together with Tikhonov regularization. Besides setting up the objective function with a regularizing member, the authors also specify the differentiation equation for the iterative solution of the inverse problem via the Gauss-Newton method. Further, the time consumption of computing the Jacobian via a CPU compared to using a newly assembled program that exploits GPU-based parallel processing is investigated in detail. The program, utilizing the NVIDIA CUDA platform, employs parallelized computation of the individual columns of the Jacobi matrix, and this approach proved to be twenty times faster than the CPU-based sequential processing.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20201 - Electrical and electronic engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

PIERS Proceedings (Spring) 2017

ISBN

978-1-5090-6269-0

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

1710-1714

Název nakladatele

Neuveden

Místo vydání

neuveden

Místo konání akce

Petrohrad

Datum konání akce

22. 5. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000427596701137