DISTRIBUTED VOLUME RENDERING FOR SCALABLE HIGH-RESOLUTION DISPLAY ARRAYS

Nicholas Schwarz, Jason Leigh

Abstract

This work presents a distributed image-order volume rendering approach for scalable high-resolution displays. This approach preprocesses data into a conventional hierarchical structure which is distributed across the local storage of a distributed-memory cluster. The cluster is equipped with graphics cards capable of hardware accelerated texture rendering. The novel contribution of this work is its unique data management scheme that spans both GPU and CPU memory using a multi-level cache and distributed shared-memory system. Performance results show that the system scales as output resolution and cluster size increase. An implementation of this approach allows scientists to quasi-interactively visualize large volume datasets on scalable high-resolution display arrays.This work presents a distributed image-order volume rendering approach for scalable high-resolution displays. This approach preprocesses data into a conventional hierarchical structure which is distributed across the local storage of a distributed-memory cluster. The cluster is equipped with graphics cards capable of hardware accelerated texture rendering. The novel contribution of this work is its unique data management scheme that spans both GPU and CPU memory using a multi-level cache and distributed shared-memory system. Performance results show that the system scales as output resolution and cluster size increase. An implementation of this approach allows scientists to quasi-interactively visualize large volume datasets on scalable high-resolution display arrays.This work presents a distributed image-order volume rendering approach for scalable high-resolution displays. This approach preprocesses data into a conventional hierarchical structure which is distributed across the local storage of a distributed-memory cluster. The cluster is equipped with graphics cards capable of hardware accelerated texture rendering. The novel contribution of this work is its unique data management scheme that spans both GPU and CPU memory using a multi-level cache and distributed shared-memory system. Performance results show that the system scales as output resolution and cluster size increase. An implementation of this approach allows scientists to quasi-interactively visualize large volume datasets on scalable high-resolution display arrays.

References

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Paper Citation


in Harvard Style

Schwarz N. and Leigh J. (2010). DISTRIBUTED VOLUME RENDERING FOR SCALABLE HIGH-RESOLUTION DISPLAY ARRAYS . In Proceedings of the International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2010) ISBN 978-989-674-026-9, pages 211-218. DOI: 10.5220/0002812902110218


in Bibtex Style

@conference{grapp10,
author={Nicholas Schwarz and Jason Leigh},
title={DISTRIBUTED VOLUME RENDERING FOR SCALABLE HIGH-RESOLUTION DISPLAY ARRAYS},
booktitle={Proceedings of the International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2010)},
year={2010},
pages={211-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002812902110218},
isbn={978-989-674-026-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Graphics Theory and Applications - Volume 1: GRAPP, (VISIGRAPP 2010)
TI - DISTRIBUTED VOLUME RENDERING FOR SCALABLE HIGH-RESOLUTION DISPLAY ARRAYS
SN - 978-989-674-026-9
AU - Schwarz N.
AU - Leigh J.
PY - 2010
SP - 211
EP - 218
DO - 10.5220/0002812902110218