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Accelerating stereo vision algorithm using SSE3, AVX2, and CUDA
KTH, School of Information and Communication Technology (ICT), Electronics.
2017 (English)In: 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, Institute of Electrical and Electronics Engineers (IEEE), 2017, 2194-2199 p., 7985426Conference paper (Refereed)
Abstract [en]

Stereo vision features a widespread usage such as robotics, unmanned cars, aerial surveys, and many real-time applications. Also, it needs computational expensive calculations because of stereo matching. In real time applications, the execution time of stereo vision depth detection algorithm is very important. This paper studies the Intel SIMD instructions and CUDA effects on reducing the execution time of the stereo vision. CUDA and SIMD instructions improve performance by exploiting data level parallelism. We present a fast implementation of SSD stereo vision algorithm on Intel processors using SIMD instruction sets (SSE3 and AVX2) and NVIDIA Graphics Processing Unit (GPU) using CUDA language and compare their results with serial implementation. The algorithm applied to different ranges of disparity (from 16 to 256), window size (from 3×3 to 15×15) and image resolution (from 256×212 to 1408×1168) parameters. We achieved 182 frames per second rate for the disparity of 64 and window size of 3×3 in CUDA, 64 frames per second rate in AVX2 and 25 frames per second rate in SSE3. Experimental results show that we can get speedup up to 5× in SSE3, 10× in AVX2 and 21× in CUDA compared to serial implementation.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. 2194-2199 p., 7985426
Keyword [en]
AVX2, CUDA, GPU, Intel SIMD instruction set, SSD, SSE3, Stereo vision
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-217489DOI: 10.1109/IranianCEE.2017.7985426Scopus ID: 2-s2.0-85032838288ISBN: 9781509059638 OAI: oai:DiVA.org:kth-217489DiVA: diva2:1156900
Conference
25th Iranian Conference on Electrical Engineering, ICEE 2017, K.N. Toosi University of TechnologyTehran, Iran, 2 May 2017 through 4 May 2017
Note

QC 20171114

Available from: 2017-11-14 Created: 2017-11-14 Last updated: 2017-11-14Bibliographically approved

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CiteExportLink to record
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  • apa
  • harvard1
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  • modern-language-association-8th-edition
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More styles
Language
  • de-DE
  • en-GB
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  • fi-FI
  • nn-NO
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  • Other locale
More languages
Output format
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