Vertex–transformation streams
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Youngmin Kim | - |
dc.contributor.author | Lee, Chang Ha | - |
dc.contributor.author | Amitabh Varshney | - |
dc.date.accessioned | 2023-02-22T05:42:32Z | - |
dc.date.available | 2023-02-22T05:42:32Z | - |
dc.date.issued | 2006-07 | - |
dc.identifier.issn | 1524-0703 | - |
dc.identifier.issn | 1524-0711 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/60856 | - |
dc.description.abstract | Recent trends in parallel computer architecture strongly suggest the need to improve the arithmetic intensity (the compute to bandwidth ratio) for greater performance in time-critical applications, such as interactive 3D graphics. At the same time, advances in stream programming abstraction for graphics processors (GPUs) have enabled us to use parallel algorithm design methods for GPU programming. Inspired by these developments, this paper explores the interactions between multiple data streams to improve arithmetic intensity and address the input geometry bandwidth bottleneck for interactive 3D graphics applications. We introduce the idea of creating vertex and transformation streams that represent large point datasets via their interaction. We discuss how to factor such point datasets into a set of source vertices and transformation streams by identifying the most common translations amongst vertices. We accomplish this by identifying peaks in the cross-power spectrum of the dataset in the Fourier domain. We validate our approach by integrating it with a view-dependent point rendering system and show significant improvements in input geometry bandwidth requirements as well as rendering frame rates. | - |
dc.format.extent | 13 | - |
dc.publisher | Academic Press | - |
dc.title | Vertex–transformation streams | - |
dc.type | Article | - |
dc.identifier.doi | 10.1016/j.gmod.2006.03.005 | - |
dc.identifier.bibliographicCitation | Graphical Models, v.68, no.4, pp 371 - 383 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 383 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 371 | - |
dc.citation.title | Graphical Models | - |
dc.citation.volume | 68 | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | Stream programming | - |
dc.subject.keywordAuthor | Arithmetic intensity | - |
dc.subject.keywordAuthor | Geometry instancing | - |
dc.subject.keywordAuthor | Transformation encoding | - |
dc.subject.keywordAuthor | Streaming algorithms | - |
dc.description.journalRegisteredClass | scopus | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.