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Automatic Distribution of Rendering Workloads in a Grid Enabled Collaborative Visualization Environment
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Source Conference on High Performance Networking and Computing archive
Proceedings of the 2004 ACM/IEEE conference on Supercomputing table of contents
Page: 1  
Year of Publication: 2004
ISBN:0-7695-2153-3
Authors
Ian J. Grimstead  Cardiff University
Nick J. Avis  Cardiff University
David W. Walker  Cardiff University
Sponsor
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
IEEE Computer Society  Washington, DC, USA
Bibliometrics
Downloads (6 Weeks): 6,   Downloads (12 Months): 40,   Citation Count: 6
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: 10.1109/SC.2004.13

ABSTRACT

This paper presents a distributed, collaborative grid enabled visualization environment that supports automated resource discovery across heterogeneous machines. OurResource-Aware Visualization Environment (RAVE) runs as a background process using Grid/Web services, enabling us to share resources with other users rather than commandeering an entire machine. RAVE supports a wide range of machines, from hand-held PDAs to high-end servers with large-scale stereo, tracked displays. The local display device may render all, some or none of the data set remotely, depending on its available resources. This enables scientists and engineers to collaborate from their desks, in the field or in front of specialised immersive displays. We present initial results of our implementation, showing how we distribute complete datasets across multiple machines as required, using a central data service to distribute data updates from collaborating users. We will demonstrate RAVE at SC2004, utilising available heterogeneous resources.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Ian J. Grimstead: colleagues
Nick J. Avis: colleagues
David W. Walker: colleagues