Parallel distributed, GPU-Accelerated, advanced lighting calculations for large-scale volume visualization

Min Shih, Silvio Rizzi, Joseph Insley, Thomas Uram, Venkatram Vishwanath, Mark Hereld, Michael E. Papka, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

The benefits of applying advanced illumination models to volume visualization have been demonstrated by many researchers. For a parallel distributed, GPU computing environment, however, there is no efficient algorithm for scalable global illumination calculations. This paper presents a parallel, data-distributed and GPU-Accelerated algorithm for volume rendering with advanced lighting. Our approach features tunable soft shadows for enhancing perception of complex spatial structures and relationships. For lighting calculations, our design effectively avoids data exchange among GPUS. Performance evaluation on a GPU cluster using up to 128 GPUS shows scalable rendering performance, with both the number of GPUS and volume data size.

Original languageEnglish (US)
Title of host publicationIEEE Symposium on Large Data Analysis and Visualization 2016, LDAV 2016 - Proceedings
EditorsKenneth Moreland, Markus Hadwiger, Ross Maciejewski
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages47-55
Number of pages9
ISBN (Electronic)9781509056590
DOIs
StatePublished - Mar 8 2017
Event6th IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2016 - Baltimore, United States
Duration: Oct 23 2016 → …

Other

Other6th IEEE Symposium on Large-Scale Data Analysis and Visualization, LDAV 2016
CountryUnited States
CityBaltimore
Period10/23/16 → …

ASJC Scopus subject areas

  • Computer Science Applications
  • Modeling and Simulation

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    Shih, M., Rizzi, S., Insley, J., Uram, T., Vishwanath, V., Hereld, M., Papka, M. E., & Ma, K-L. (2017). Parallel distributed, GPU-Accelerated, advanced lighting calculations for large-scale volume visualization. In K. Moreland, M. Hadwiger, & R. Maciejewski (Eds.), IEEE Symposium on Large Data Analysis and Visualization 2016, LDAV 2016 - Proceedings (pp. 47-55). [7874309] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LDAV.2016.7874309