TY - JOUR

T1 - Optimization of the GPU-based data evaluation for the low coherence interferometry

AU - Li, Yinan

AU - Kästner, Markus

AU - Reithmeier, Eduard

N1 - Funding information: Acknowledgement: The authors would like to thank the “German Research Foundation” (DFG) for funding this project A2 “Multi Scale Geometry Measurement” within the Collaborative Research Centre (CRC) 871 Regeneration of Complex Goods (http://www.sfb871.de).

PY - 2017/10/17

Y1 - 2017/10/17

N2 - Optical interferometers as non-contact measurement devices are very desirable for the measurement of surface roughness and topography. Compared to phase shifting interferometers (PSIs) with a limited measurement range and a scan step of maximum λ/4, the optical interferometers like low coherence interferometers (LCIs) evaluating the degree of fringe coherence allow a larger vertical measurement range. Their vertical measurement range is only limited by the scan length allowed by the linear piezo stage and the coherence length of the light source. To evaluate the obtained data for a large range, the common LCIs require much computation time. To overcome this drawback, we present an evaluation algorithm based on the Hilbert-Transform and curve fitting (Levenberg-Marquardt algorithm) using Compute Unified Device Architecture (CUDA) technology, which allows parallel and independent data evaluation on General Purpose Graphics Processing Unit (GPGPU). Firstly, the evaluation algorithm is implemented and tested on an in-house developed LCI, which is based on Michelson configurations. Furthermore, we focus on the performance optimization of the GPU-based program using the different approaches to further achieve efficient and accurate massive parallel computing. Finally, the performance comparison for evaluating measurement data using different approaches is discussed in this paper.

AB - Optical interferometers as non-contact measurement devices are very desirable for the measurement of surface roughness and topography. Compared to phase shifting interferometers (PSIs) with a limited measurement range and a scan step of maximum λ/4, the optical interferometers like low coherence interferometers (LCIs) evaluating the degree of fringe coherence allow a larger vertical measurement range. Their vertical measurement range is only limited by the scan length allowed by the linear piezo stage and the coherence length of the light source. To evaluate the obtained data for a large range, the common LCIs require much computation time. To overcome this drawback, we present an evaluation algorithm based on the Hilbert-Transform and curve fitting (Levenberg-Marquardt algorithm) using Compute Unified Device Architecture (CUDA) technology, which allows parallel and independent data evaluation on General Purpose Graphics Processing Unit (GPGPU). Firstly, the evaluation algorithm is implemented and tested on an in-house developed LCI, which is based on Michelson configurations. Furthermore, we focus on the performance optimization of the GPU-based program using the different approaches to further achieve efficient and accurate massive parallel computing. Finally, the performance comparison for evaluating measurement data using different approaches is discussed in this paper.

KW - interferometry

KW - Optical measurement technology

KW - parallel computing

KW - surface measurement

UR - http://www.scopus.com/inward/record.url?scp=85037627732&partnerID=8YFLogxK

U2 - 10.1515/teme-2017-0091

DO - 10.1515/teme-2017-0091

M3 - Article

AN - SCOPUS:85037627732

VL - 85

SP - 680

EP - 690

JO - TM. Technisches Messen

JF - TM. Technisches Messen

SN - 0171-8096

IS - 11

ER -