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| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Equalizer: A scalable parallel rendering framework |
| Organization Unit | |
| Authors |
|
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | IEEE Transactions on Visualization and Computer Graphics |
| Publisher | IEEE |
| Geographical Reach | international |
| ISSN | 1077-2626 |
| Volume | 15 |
| Number | 3 |
| Page Range | 436 - 452 |
| Date | 2009 |
| Abstract Text | Continuing improvements in CPU and GPU performances as well as increasing multi-core processor and cluster-based parallelism demand for flexible and scalable parallel rendering solutions that can exploit multipipe hardware accelerated graphics. In fact, to achieve interactive visualization, scalable rendering systems are essential to cope with the rapid growth of data sets. However, parallel rendering systems are non-trivial to develop and often only application specific implementations have been proposed. The task of developing a scalable parallel rendering framework is even more difficult if it should be generic to support various types of data and visualization applications, and at the same time work efficiently on a cluster with distributed graphics cards. In this paper we introduce a novel system called Equalizer, a toolkit for scalable parallel rendering based on OpenGL which provides an application programming interface (API) to develop scalable graphics applications for a wide range of systems ranging from large distributed visualization clusters and multi-processor multipipe graphics systems to single-processor single-pipe desktop machines. We describe the system architecture, the basic API, discuss its advantages over previous approaches, present example configurations and usage scenarios as well as scalability results. |
| Digital Object Identifier | 10.1109/TVCG.2008.104 |
| PubMed ID | 19282550 |
| Other Identification Number | merlin-id:218 |
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| Additional Information | © 2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE |