Efficient PRAM and Practical GPU Algorithms for Large Polygon Clipping with Degenerate Cases
Polygonal geometric operations are fundamental in domains such as Computer Graphics, Computer-Aided Design, and Geographic Information Systems. Handling degenerate cases in such operations is important when real-world spatial data are used. The popular Greiner-Hormann (GH) clipping algorithm does no...
Gespeichert in:
| Veröffentlicht in: | 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid) S. 579 - 591 |
|---|---|
| Hauptverfasser: | , , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
01.05.2023
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | Polygonal geometric operations are fundamental in domains such as Computer Graphics, Computer-Aided Design, and Geographic Information Systems. Handling degenerate cases in such operations is important when real-world spatial data are used. The popular Greiner-Hormann (GH) clipping algorithm does not handle such cases properly without perturbing vertices leading to inaccuracies and ambiguities. In this work, we parallelize the O (n 2 )-time general polygon clipping algorithm by Foster et al., which can handle degenerate cases without perturbation. Our CREW PRAM algorithm can perform clipping in O (log n) time using n + k number of processors with simple polygons, where n is the number of input edges and k is the number of edge intersections. For efficient GPU implementation, we employ three effective filters which have not been used in prior work on polygon clipping: 1) Common-minimum-bounding-rectangle filter, 2) Count-based filter, and 3) Line-segment-minimum-bounding-rectangle filter. They drastically reduce O( n 2 ) candidate edge pairs comparisons by 80% - 99%, leading to significantly faster parallel execution. In our experiments, C++ CUDA-based implementation yields up to 40X speedup over real-world datasets, processing two polygons with a total of 174K vertices on an Nvidia Quadro RTX 5000 GPU compared to the sequential Foster's algorithm running on an Intel Xeon Silver 4210R CPU. |
|---|---|
| AbstractList | Polygonal geometric operations are fundamental in domains such as Computer Graphics, Computer-Aided Design, and Geographic Information Systems. Handling degenerate cases in such operations is important when real-world spatial data are used. The popular Greiner-Hormann (GH) clipping algorithm does not handle such cases properly without perturbing vertices leading to inaccuracies and ambiguities. In this work, we parallelize the O (n 2 )-time general polygon clipping algorithm by Foster et al., which can handle degenerate cases without perturbation. Our CREW PRAM algorithm can perform clipping in O (log n) time using n + k number of processors with simple polygons, where n is the number of input edges and k is the number of edge intersections. For efficient GPU implementation, we employ three effective filters which have not been used in prior work on polygon clipping: 1) Common-minimum-bounding-rectangle filter, 2) Count-based filter, and 3) Line-segment-minimum-bounding-rectangle filter. They drastically reduce O( n 2 ) candidate edge pairs comparisons by 80% - 99%, leading to significantly faster parallel execution. In our experiments, C++ CUDA-based implementation yields up to 40X speedup over real-world datasets, processing two polygons with a total of 174K vertices on an Nvidia Quadro RTX 5000 GPU compared to the sequential Foster's algorithm running on an Intel Xeon Silver 4210R CPU. |
| Author | Ashan, M. K. Buddhi Puri, Satish Prasad, Sushil K. |
| Author_xml | – sequence: 1 givenname: M. K. Buddhi surname: Ashan fullname: Ashan, M. K. Buddhi email: buddhiashan.mallikakankanamalage@utsa.edu organization: University of Texas at,Department of Computer Science,San Antonio – sequence: 2 givenname: Satish surname: Puri fullname: Puri, Satish email: satish.puri@marquette.edu organization: Marquette University,Department of Computer Science – sequence: 3 givenname: Sushil K. surname: Prasad fullname: Prasad, Sushil K. email: sushil.prasad@utsa.edu organization: University of Texas at,Department of Computer Science,San Antonio |
| BookMark | eNotjNFKwzAUQCPog879gUh-YPXeJGuTx1JnJ1Qs4t6EceluaqBLR1qQ_b0DfTocOJw7cR3HyEI8ImSI4J6qqk7hsC5yqzIFSmcAkMOVWLrCWb0GDYjO3YqvjfehCxxn2X6Ub5LiQbaJujl0NMi63cly6McU5u_jJP2YZEOpZ9mOw7kfo6yGcDqF2MufSyGfuefIiWaWFU083YsbT8PEy38uxO5l81ltV817_VqVzSooMPPqAMp4q_KOFKJH5ZjQoPXKOdbkjDWeCw_GYgfeFoZIX8wBIbFXCvRCPPx9AzPvTykcKZ33CFjgOrf6F3IdUNo |
| CODEN | IEEPAD |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/CCGrid57682.2023.00060 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings Accès Toulouse INP et ENVT - IEEE Xplore POP ALL IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Xplore url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798350301199 |
| EndPage | 591 |
| ExternalDocumentID | 10171568 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i204t-d024f826ca211f129ea1418f299e3a9484fe7f0481c0f874aa3f0490a1aef2203 |
| IEDL.DBID | RIE |
| ISICitedReferencesCount | 2 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001031746200050&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| IngestDate | Thu Jan 18 11:14:47 EST 2024 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i204t-d024f826ca211f129ea1418f299e3a9484fe7f0481c0f874aa3f0490a1aef2203 |
| PageCount | 13 |
| ParticipantIDs | ieee_primary_10171568 |
| PublicationCentury | 2000 |
| PublicationDate | 2023-May |
| PublicationDateYYYYMMDD | 2023-05-01 |
| PublicationDate_xml | – month: 05 year: 2023 text: 2023-May |
| PublicationDecade | 2020 |
| PublicationTitle | 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid) |
| PublicationTitleAbbrev | CCGRID |
| PublicationYear | 2023 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.845336 |
| Snippet | Polygonal geometric operations are fundamental in domains such as Computer Graphics, Computer-Aided Design, and Geographic Information Systems. Handling... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 579 |
| SubjectTerms | C++ languages Clustering algorithms degenerate intersections Filtering algorithms Foster et al. algorithm GPU algorithm Graphics processing units Greiner-Hormann algorithm Perturbation methods Phase change random access memory polygon clipping PRAM algorithm Silver |
| Title | Efficient PRAM and Practical GPU Algorithms for Large Polygon Clipping with Degenerate Cases |
| URI | https://ieeexplore.ieee.org/document/10171568 |
| WOSCitedRecordID | wos001031746200050&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PS8MwFA5uePCk4sTf5OC1rk3TNjmOus3DHEUc7CCMrHmpg9mOrRP8731J54-LB28hEAIvge99yfu-R8itCSMTq2iOlxeUx1WgPMzjmIdYK6IIINbSCYVHyXgsplOZ7cTqTgsDAK74DO7s0P3l6yrf2qeyrr0-yDdEi7SSJGnEWjvVb-DLbpoO1wttE2irsGLWutS31pO_2qY41Bgc_nO_I9L50d_R7BtZjskelCfkpe_cHnAFzZ56j1SVmjZuQxhmOswmtLcsKuT6r28biqkoHdkib5pVy4-iKmm6dFYMBbUvr_QeCuc3XQNNEcc2HTIZ9J_TB2_XG8FbMJ_XnkZsNUgNcoUMziBogwp4IAyiC4RKcsENJMaaweS-EQlXKjT2kw8PAwxjfnhK2mVVwhmhPoQy0JrFOkf6EksRR8EcmERMkwCKn5OODc1s1dhfzL6icvHH_CU5sNFvqgKvSLteb-Ga7Ofv9WKzvnGH9gmyD5kX |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1dS8MwFA06BX1SceK3efC1rk3TrnkcdR9iN4pssAdhZM3NHMxWtk7w33uTzo8XH3wLgRC4N3DuSe45IeRW-4EOZTDFwwvS4dKTDtZxzEGsjYIAIFTCCoWT5mAQjcci3YjVrRYGAGzzGdyZoX3LV0W2NldlDXN8kG9E22Qn4Jx5lVxro_v1XNGI4-5yrkwJbTRWzJiXusZ88tfHKRY3Ogf_3PGQ1H8UeDT9xpYjsgX5MXluW78HXEHTp1afylzRym8IA0276Yi2FrMC2f7L64piMUoT0-ZN02LxMStyGi-sGcOMmrtXeg8z6zhdAo0RyVZ1Muq0h3HP2fyO4MyZy0tHIbpqJAeZRA6nEbZBetyLNOIL-FLwiGtoamMHk7k6anIpfW2e-TAdoBlz_RNSy4scTgl1wReeUixUGRKYUERh4E2BCUQ1ASD5Gamb0EzeKgOMyVdUzv-YvyF7vWE_mSQPg8cLsm8yUfUIXpJauVzDFdnN3sv5anltE_gJ2Q6cXg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2023+IEEE%2FACM+23rd+International+Symposium+on+Cluster%2C+Cloud+and+Internet+Computing+%28CCGrid%29&rft.atitle=Efficient+PRAM+and+Practical+GPU+Algorithms+for+Large+Polygon+Clipping+with+Degenerate+Cases&rft.au=Ashan%2C+M.+K.+Buddhi&rft.au=Puri%2C+Satish&rft.au=Prasad%2C+Sushil+K.&rft.date=2023-05-01&rft.pub=IEEE&rft.spage=579&rft.epage=591&rft_id=info:doi/10.1109%2FCCGrid57682.2023.00060&rft.externalDocID=10171568 |