Understanding Next-generation VR: Classifying Commodity Clusters for Immersive Virtual Reality

Streit, Alexander T., Christie, Ruth J., & Boud, Andy (2004) Understanding Next-generation VR: Classifying Commodity Clusters for Immersive Virtual Reality. In Spencer, Steven N. (Ed.) 2nd international conference on Computer graphics and interactive techniques in Australasia and South East Asia, June 15-18, Singapore.

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Commodity clusters offer the ability to deliver higher performance computer graphics at lower prices than traditional graphics supercomputers. Immersive virtual reality systems demand notoriously high computational requirements to deliver adequate real-time graphics, leading to the emergence of commodity clusters for immersive virtual reality. Such clusters deliver the graphics power needed by leveraging the combined power of several computers to meet the demands of real-time interactive immersive computer graphics.However, the field of commodity cluster-based virtual reality is still in early stages of development and the field is currently adhoc in nature and lacks order. There is no accepted means for comparing approaches and implementers are left with instinctual or trial-and-error means for selecting an approach.This paper provides a classification system that facilitates understanding not only of the nature of different clustering systems but also the interrelations between them. The system is built from a new model for generalized computer graphics applications, which is based on the flow of data through a sequence of operations over the entire context of the application. Prior models and classification systems have been too focused in context and application whereas the system described here provides a unified means for comparison of works within the field.

Impact and interest:

4 citations in Scopus
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ID Code: 1936
Item Type: Conference Paper
Refereed: Yes
Keywords: Virtual Reality, Classification, Ontology, Computer Clusters, Graphics Clusters
DOI: 10.1145/988834.988872
ISBN: 1581138830
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Virtual Reality and Related Simulation (080111)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2004 ACM
Copyright Statement: Reproduced in accordance with the copyright policy of the publisher.
Deposited On: 16 Aug 2005 00:00
Last Modified: 29 Feb 2012 13:06

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