GPU Pathfinding Optimization
In recent years, GPUs (Graphics Processing Units) have shown a significant advance of computational resources available for the use of non-graphical applications. The ability to solve problems involving parallel computing as well as the development of new architectures that supports this new paradig...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 163 |
|---|---|
| container_issue | |
| container_start_page | 158 |
| container_title | |
| container_volume | |
| creator | Silva, A. Rocha, F. Santos, A. Ramalho, G. Teichrieb, V. |
| description | In recent years, GPUs (Graphics Processing Units) have shown a significant advance of computational resources available for the use of non-graphical applications. The ability to solve problems involving parallel computing as well as the development of new architectures that supports this new paradigm, such as CUDA (Compute Unified Device Architecture), have encouraged the use of GPU for general purpose applications, especially in games. Some parallel tasks which were CPU (Central Processing Unit) based are being ported over to the GPU due to theirs superior performance. One of these tasks is the path finding of an agent over a game map, which has already achieved a better performance on GPU, but is still limited. This paper describes some optimizations to a GPU path finding implementation, addressing larger work set (agents and nodes) with good performance. |
| doi_str_mv | 10.1109/SBGAMES.2011.35 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6363229</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6363229</ieee_id><sourcerecordid>6363229</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-30419deda3c4fd425ea58dc9bc672997c9f5ae68c30fb84acb3e0ccfacede73f3</originalsourceid><addsrcrecordid>eNotzM1OAjEUQOEaNZHgrF3oghcYvO3t310igdEEAwm4Jp32VmtkJMxs9OlN1NXJtzlC3EiYSgl0v31oZs-L7VSBlFM0Z6Ii58FZMtpqj-e_lto6BEcOLsRISUO1tUZfiarv3wEApXOk_UjcNZuXySYMb7l0qXSvk_VxKIfyHYby2V2Lyxw-eq7-Oxa75WI3f6xX6-ZpPlvVhWCoEbSkxClg1DlpZTgYnyK10TpF5CJlE9j6iJBbr0NskSHGHCIndphxLG7_toWZ98dTOYTT196iRaUIfwCqw0C-</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>GPU Pathfinding Optimization</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Silva, A. ; Rocha, F. ; Santos, A. ; Ramalho, G. ; Teichrieb, V.</creator><creatorcontrib>Silva, A. ; Rocha, F. ; Santos, A. ; Ramalho, G. ; Teichrieb, V.</creatorcontrib><description>In recent years, GPUs (Graphics Processing Units) have shown a significant advance of computational resources available for the use of non-graphical applications. The ability to solve problems involving parallel computing as well as the development of new architectures that supports this new paradigm, such as CUDA (Compute Unified Device Architecture), have encouraged the use of GPU for general purpose applications, especially in games. Some parallel tasks which were CPU (Central Processing Unit) based are being ported over to the GPU due to theirs superior performance. One of these tasks is the path finding of an agent over a game map, which has already achieved a better performance on GPU, but is still limited. This paper describes some optimizations to a GPU path finding implementation, addressing larger work set (agents and nodes) with good performance.</description><identifier>ISSN: 2159-6654</identifier><identifier>ISBN: 9781467307970</identifier><identifier>ISBN: 1467307971</identifier><identifier>EISBN: 9780769546483</identifier><identifier>EISBN: 076954648X</identifier><identifier>DOI: 10.1109/SBGAMES.2011.35</identifier><identifier>CODEN: IEEPAD</identifier><language>eng</language><publisher>IEEE</publisher><subject>Computer architecture ; CUDA ; Games ; GPU ; Graphics processing units ; Instruction sets ; intelligent agents ; Kernel ; Optimization ; Parallel processing ; pathfinding</subject><ispartof>2011 Brazilian Symposium on Games and Digital Entertainment, 2011, p.158-163</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6363229$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,778,782,787,788,2054,27912,54907</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6363229$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Silva, A.</creatorcontrib><creatorcontrib>Rocha, F.</creatorcontrib><creatorcontrib>Santos, A.</creatorcontrib><creatorcontrib>Ramalho, G.</creatorcontrib><creatorcontrib>Teichrieb, V.</creatorcontrib><title>GPU Pathfinding Optimization</title><title>2011 Brazilian Symposium on Games and Digital Entertainment</title><addtitle>sbgames</addtitle><description>In recent years, GPUs (Graphics Processing Units) have shown a significant advance of computational resources available for the use of non-graphical applications. The ability to solve problems involving parallel computing as well as the development of new architectures that supports this new paradigm, such as CUDA (Compute Unified Device Architecture), have encouraged the use of GPU for general purpose applications, especially in games. Some parallel tasks which were CPU (Central Processing Unit) based are being ported over to the GPU due to theirs superior performance. One of these tasks is the path finding of an agent over a game map, which has already achieved a better performance on GPU, but is still limited. This paper describes some optimizations to a GPU path finding implementation, addressing larger work set (agents and nodes) with good performance.</description><subject>Computer architecture</subject><subject>CUDA</subject><subject>Games</subject><subject>GPU</subject><subject>Graphics processing units</subject><subject>Instruction sets</subject><subject>intelligent agents</subject><subject>Kernel</subject><subject>Optimization</subject><subject>Parallel processing</subject><subject>pathfinding</subject><issn>2159-6654</issn><isbn>9781467307970</isbn><isbn>1467307971</isbn><isbn>9780769546483</isbn><isbn>076954648X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotzM1OAjEUQOEaNZHgrF3oghcYvO3t310igdEEAwm4Jp32VmtkJMxs9OlN1NXJtzlC3EiYSgl0v31oZs-L7VSBlFM0Z6Ii58FZMtpqj-e_lto6BEcOLsRISUO1tUZfiarv3wEApXOk_UjcNZuXySYMb7l0qXSvk_VxKIfyHYby2V2Lyxw-eq7-Oxa75WI3f6xX6-ZpPlvVhWCoEbSkxClg1DlpZTgYnyK10TpF5CJlE9j6iJBbr0NskSHGHCIndphxLG7_toWZ98dTOYTT196iRaUIfwCqw0C-</recordid><startdate>201111</startdate><enddate>201111</enddate><creator>Silva, A.</creator><creator>Rocha, F.</creator><creator>Santos, A.</creator><creator>Ramalho, G.</creator><creator>Teichrieb, V.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201111</creationdate><title>GPU Pathfinding Optimization</title><author>Silva, A. ; Rocha, F. ; Santos, A. ; Ramalho, G. ; Teichrieb, V.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-30419deda3c4fd425ea58dc9bc672997c9f5ae68c30fb84acb3e0ccfacede73f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Computer architecture</topic><topic>CUDA</topic><topic>Games</topic><topic>GPU</topic><topic>Graphics processing units</topic><topic>Instruction sets</topic><topic>intelligent agents</topic><topic>Kernel</topic><topic>Optimization</topic><topic>Parallel processing</topic><topic>pathfinding</topic><toplevel>online_resources</toplevel><creatorcontrib>Silva, A.</creatorcontrib><creatorcontrib>Rocha, F.</creatorcontrib><creatorcontrib>Santos, A.</creatorcontrib><creatorcontrib>Ramalho, G.</creatorcontrib><creatorcontrib>Teichrieb, V.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Silva, A.</au><au>Rocha, F.</au><au>Santos, A.</au><au>Ramalho, G.</au><au>Teichrieb, V.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>GPU Pathfinding Optimization</atitle><btitle>2011 Brazilian Symposium on Games and Digital Entertainment</btitle><stitle>sbgames</stitle><date>2011-11</date><risdate>2011</risdate><spage>158</spage><epage>163</epage><pages>158-163</pages><issn>2159-6654</issn><isbn>9781467307970</isbn><isbn>1467307971</isbn><eisbn>9780769546483</eisbn><eisbn>076954648X</eisbn><coden>IEEPAD</coden><abstract>In recent years, GPUs (Graphics Processing Units) have shown a significant advance of computational resources available for the use of non-graphical applications. The ability to solve problems involving parallel computing as well as the development of new architectures that supports this new paradigm, such as CUDA (Compute Unified Device Architecture), have encouraged the use of GPU for general purpose applications, especially in games. Some parallel tasks which were CPU (Central Processing Unit) based are being ported over to the GPU due to theirs superior performance. One of these tasks is the path finding of an agent over a game map, which has already achieved a better performance on GPU, but is still limited. This paper describes some optimizations to a GPU path finding implementation, addressing larger work set (agents and nodes) with good performance.</abstract><pub>IEEE</pub><doi>10.1109/SBGAMES.2011.35</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 2159-6654 |
| ispartof | 2011 Brazilian Symposium on Games and Digital Entertainment, 2011, p.158-163 |
| issn | 2159-6654 |
| language | eng |
| recordid | cdi_ieee_primary_6363229 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Computer architecture CUDA Games GPU Graphics processing units Instruction sets intelligent agents Kernel Optimization Parallel processing pathfinding |
| title | GPU Pathfinding Optimization |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T16%3A52%3A57IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=GPU%20Pathfinding%20Optimization&rft.btitle=2011%20Brazilian%20Symposium%20on%20Games%20and%20Digital%20Entertainment&rft.au=Silva,%20A.&rft.date=2011-11&rft.spage=158&rft.epage=163&rft.pages=158-163&rft.issn=2159-6654&rft.isbn=9781467307970&rft.isbn_list=1467307971&rft.coden=IEEPAD&rft_id=info:doi/10.1109/SBGAMES.2011.35&rft_dat=%3Cieee_6IE%3E6363229%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9780769546483&rft.eisbn_list=076954648X&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6363229&rfr_iscdi=true |