Parallel Computer System for 3D Visualization Stereo on GPU

This paper proposes the organization of a parallel computer system based on Graphic Processors Unit (GPU) for 3D stereo image synthesis. The development is based on the modified ray tracing method developed by the authors for fast search of tracing rays intersections with scene objects. The system a...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:3D research 2018-03, Vol.9 (1), p.1-13, Article 7
Hauptverfasser: Al-Oraiqat, Anas M., Zori, Sergii A.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 13
container_issue 1
container_start_page 1
container_title 3D research
container_volume 9
creator Al-Oraiqat, Anas M.
Zori, Sergii A.
description This paper proposes the organization of a parallel computer system based on Graphic Processors Unit (GPU) for 3D stereo image synthesis. The development is based on the modified ray tracing method developed by the authors for fast search of tracing rays intersections with scene objects. The system allows significant increase in the productivity for the 3D stereo synthesis of photorealistic quality. The generalized procedure of 3D stereo image synthesis on the Graphics Processing Unit/Graphics Processing Clusters (GPU/GPC) is proposed. The efficiency of the proposed solutions by GPU implementation is compared with single-threaded and multithreaded implementations on the CPU. The achieved average acceleration in multi-thread implementation on the test GPU and CPU is about 7.5 and 1.6 times, respectively. Studying the influence of choosing the size and configuration of the computational Compute Unified Device Archi-tecture (CUDA) network on the computational speed shows the importance of their correct selection. The obtained experimental estimations can be significantly improved by new GPUs with a large number of processing cores and multiprocessors, as well as optimized configuration of the computing CUDA network.
doi_str_mv 10.1007/s13319-018-0159-x
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1993789946</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1993789946</sourcerecordid><originalsourceid>FETCH-LOGICAL-c316t-28bbaf5dce41bf24eeb7826700e69f045639f1cf1637882b201d4087765d96263</originalsourceid><addsrcrecordid>eNp1kEFLAzEQhYMoWLQ_wFvA8-pMspts8CRVq1CwUOs1ZLeJbNk2NdmF1l9vynroxcMw7_C9N8wj5AbhDgHkfUTOUWWAZZpCZfszMmKgWCYkx_MTfUnGMa4BEskwV2xEHuYmmLa1LZ34za7vbKCLQ-zshjofKH-in03sTdv8mK7xW7pIgPU0qel8eU0unGmjHf_tK7J8ef6YvGaz9-nb5HGW1RxFl7GyqowrVrXNsXIst7aSJRMSwArlIC8EVw5rh4LLsmQVA1zlUEopipUSTPArcjvk7oL_7m3s9Nr3YZtOalQqmZTKjxQOVB18jME6vQvNxoSDRtDHmvRQk07P62NNep88bPDExG6_bDhJ_tf0C1ataHo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1993789946</pqid></control><display><type>article</type><title>Parallel Computer System for 3D Visualization Stereo on GPU</title><source>SpringerLink Journals</source><creator>Al-Oraiqat, Anas M. ; Zori, Sergii A.</creator><creatorcontrib>Al-Oraiqat, Anas M. ; Zori, Sergii A.</creatorcontrib><description>This paper proposes the organization of a parallel computer system based on Graphic Processors Unit (GPU) for 3D stereo image synthesis. The development is based on the modified ray tracing method developed by the authors for fast search of tracing rays intersections with scene objects. The system allows significant increase in the productivity for the 3D stereo synthesis of photorealistic quality. The generalized procedure of 3D stereo image synthesis on the Graphics Processing Unit/Graphics Processing Clusters (GPU/GPC) is proposed. The efficiency of the proposed solutions by GPU implementation is compared with single-threaded and multithreaded implementations on the CPU. The achieved average acceleration in multi-thread implementation on the test GPU and CPU is about 7.5 and 1.6 times, respectively. Studying the influence of choosing the size and configuration of the computational Compute Unified Device Archi-tecture (CUDA) network on the computational speed shows the importance of their correct selection. The obtained experimental estimations can be significantly improved by new GPUs with a large number of processing cores and multiprocessors, as well as optimized configuration of the computing CUDA network.</description><identifier>ISSN: 2092-6731</identifier><identifier>EISSN: 2092-6731</identifier><identifier>DOI: 10.1007/s13319-018-0159-x</identifier><language>eng</language><publisher>Seoul: 3D Display Research Center</publisher><subject>3DR Express ; Computation ; Computer Imaging ; Configurations ; Engineering ; Graphics boards ; Graphics processing units ; Intersections ; Lasers ; Optical Devices ; Optics ; Pattern Recognition and Graphics ; Photonics ; Processors ; Ray tracing ; Signal,Image and Speech Processing ; Synthesis ; Vision</subject><ispartof>3D research, 2018-03, Vol.9 (1), p.1-13, Article 7</ispartof><rights>3D Research Center, Kwangwoon University and Springer-Verlag GmbH Germany, part of Springer Nature 2018</rights><rights>Copyright Springer Science &amp; Business Media 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-28bbaf5dce41bf24eeb7826700e69f045639f1cf1637882b201d4087765d96263</citedby><cites>FETCH-LOGICAL-c316t-28bbaf5dce41bf24eeb7826700e69f045639f1cf1637882b201d4087765d96263</cites><orcidid>0000-0002-1071-6331</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s13319-018-0159-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s13319-018-0159-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27903,27904,41467,42536,51297</link.rule.ids></links><search><creatorcontrib>Al-Oraiqat, Anas M.</creatorcontrib><creatorcontrib>Zori, Sergii A.</creatorcontrib><title>Parallel Computer System for 3D Visualization Stereo on GPU</title><title>3D research</title><addtitle>3D Res</addtitle><description>This paper proposes the organization of a parallel computer system based on Graphic Processors Unit (GPU) for 3D stereo image synthesis. The development is based on the modified ray tracing method developed by the authors for fast search of tracing rays intersections with scene objects. The system allows significant increase in the productivity for the 3D stereo synthesis of photorealistic quality. The generalized procedure of 3D stereo image synthesis on the Graphics Processing Unit/Graphics Processing Clusters (GPU/GPC) is proposed. The efficiency of the proposed solutions by GPU implementation is compared with single-threaded and multithreaded implementations on the CPU. The achieved average acceleration in multi-thread implementation on the test GPU and CPU is about 7.5 and 1.6 times, respectively. Studying the influence of choosing the size and configuration of the computational Compute Unified Device Archi-tecture (CUDA) network on the computational speed shows the importance of their correct selection. The obtained experimental estimations can be significantly improved by new GPUs with a large number of processing cores and multiprocessors, as well as optimized configuration of the computing CUDA network.</description><subject>3DR Express</subject><subject>Computation</subject><subject>Computer Imaging</subject><subject>Configurations</subject><subject>Engineering</subject><subject>Graphics boards</subject><subject>Graphics processing units</subject><subject>Intersections</subject><subject>Lasers</subject><subject>Optical Devices</subject><subject>Optics</subject><subject>Pattern Recognition and Graphics</subject><subject>Photonics</subject><subject>Processors</subject><subject>Ray tracing</subject><subject>Signal,Image and Speech Processing</subject><subject>Synthesis</subject><subject>Vision</subject><issn>2092-6731</issn><issn>2092-6731</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kEFLAzEQhYMoWLQ_wFvA8-pMspts8CRVq1CwUOs1ZLeJbNk2NdmF1l9vynroxcMw7_C9N8wj5AbhDgHkfUTOUWWAZZpCZfszMmKgWCYkx_MTfUnGMa4BEskwV2xEHuYmmLa1LZ34za7vbKCLQ-zshjofKH-in03sTdv8mK7xW7pIgPU0qel8eU0unGmjHf_tK7J8ef6YvGaz9-nb5HGW1RxFl7GyqowrVrXNsXIst7aSJRMSwArlIC8EVw5rh4LLsmQVA1zlUEopipUSTPArcjvk7oL_7m3s9Nr3YZtOalQqmZTKjxQOVB18jME6vQvNxoSDRtDHmvRQk07P62NNep88bPDExG6_bDhJ_tf0C1ataHo</recordid><startdate>20180301</startdate><enddate>20180301</enddate><creator>Al-Oraiqat, Anas M.</creator><creator>Zori, Sergii A.</creator><general>3D Display Research Center</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><orcidid>https://orcid.org/0000-0002-1071-6331</orcidid></search><sort><creationdate>20180301</creationdate><title>Parallel Computer System for 3D Visualization Stereo on GPU</title><author>Al-Oraiqat, Anas M. ; Zori, Sergii A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-28bbaf5dce41bf24eeb7826700e69f045639f1cf1637882b201d4087765d96263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>3DR Express</topic><topic>Computation</topic><topic>Computer Imaging</topic><topic>Configurations</topic><topic>Engineering</topic><topic>Graphics boards</topic><topic>Graphics processing units</topic><topic>Intersections</topic><topic>Lasers</topic><topic>Optical Devices</topic><topic>Optics</topic><topic>Pattern Recognition and Graphics</topic><topic>Photonics</topic><topic>Processors</topic><topic>Ray tracing</topic><topic>Signal,Image and Speech Processing</topic><topic>Synthesis</topic><topic>Vision</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Al-Oraiqat, Anas M.</creatorcontrib><creatorcontrib>Zori, Sergii A.</creatorcontrib><collection>CrossRef</collection><jtitle>3D research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Al-Oraiqat, Anas M.</au><au>Zori, Sergii A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Parallel Computer System for 3D Visualization Stereo on GPU</atitle><jtitle>3D research</jtitle><stitle>3D Res</stitle><date>2018-03-01</date><risdate>2018</risdate><volume>9</volume><issue>1</issue><spage>1</spage><epage>13</epage><pages>1-13</pages><artnum>7</artnum><issn>2092-6731</issn><eissn>2092-6731</eissn><abstract>This paper proposes the organization of a parallel computer system based on Graphic Processors Unit (GPU) for 3D stereo image synthesis. The development is based on the modified ray tracing method developed by the authors for fast search of tracing rays intersections with scene objects. The system allows significant increase in the productivity for the 3D stereo synthesis of photorealistic quality. The generalized procedure of 3D stereo image synthesis on the Graphics Processing Unit/Graphics Processing Clusters (GPU/GPC) is proposed. The efficiency of the proposed solutions by GPU implementation is compared with single-threaded and multithreaded implementations on the CPU. The achieved average acceleration in multi-thread implementation on the test GPU and CPU is about 7.5 and 1.6 times, respectively. Studying the influence of choosing the size and configuration of the computational Compute Unified Device Archi-tecture (CUDA) network on the computational speed shows the importance of their correct selection. The obtained experimental estimations can be significantly improved by new GPUs with a large number of processing cores and multiprocessors, as well as optimized configuration of the computing CUDA network.</abstract><cop>Seoul</cop><pub>3D Display Research Center</pub><doi>10.1007/s13319-018-0159-x</doi><tpages>13</tpages><orcidid>https://orcid.org/0000-0002-1071-6331</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 2092-6731
ispartof 3D research, 2018-03, Vol.9 (1), p.1-13, Article 7
issn 2092-6731
2092-6731
language eng
recordid cdi_proquest_journals_1993789946
source SpringerLink Journals
subjects 3DR Express
Computation
Computer Imaging
Configurations
Engineering
Graphics boards
Graphics processing units
Intersections
Lasers
Optical Devices
Optics
Pattern Recognition and Graphics
Photonics
Processors
Ray tracing
Signal,Image and Speech Processing
Synthesis
Vision
title Parallel Computer System for 3D Visualization Stereo on GPU
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-24T01%3A23%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Parallel%20Computer%20System%20for%203D%20Visualization%20Stereo%20on%20GPU&rft.jtitle=3D%20research&rft.au=Al-Oraiqat,%20Anas%20M.&rft.date=2018-03-01&rft.volume=9&rft.issue=1&rft.spage=1&rft.epage=13&rft.pages=1-13&rft.artnum=7&rft.issn=2092-6731&rft.eissn=2092-6731&rft_id=info:doi/10.1007/s13319-018-0159-x&rft_dat=%3Cproquest_cross%3E1993789946%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1993789946&rft_id=info:pmid/&rfr_iscdi=true