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HORT: Hadoop online ray tracing with mapreduce

Published: 07 August 2011 Publication History

Abstract

High quality computer-generated imagery (CGI) rendering is a demanding computational task [Hearn and Baker 1997]. To generate high-quality CGI, film studios rely on expensive, specialized, rendering clusters (render farms) [Rath 2009]. Render farms cost a premium over more general infrastructure such as infrastructure as a service (IaaS) offerings. Furthermore, render farms often provide limited selection of commercial rendering applications and have significant overhead with respect to requesting a job. This contrasts general IaaS offerings such as Amazon's Elastic Compute Cloud (EC2), which allows for straight-forward, automated provisioning of many virtualized machine instances.

References

[1]
Bialecki, A., et al., 2005. Hadoop: a framework for running applications on large clusters built of commodity hardware. http://lucene.apache.org/hadoop.
[2]
Dean, J., and Ghemawat, S. 2008. MapReduce: Simplified data processing on large clusters. Communications of the ACM 51, 1, 107--113.
[3]
Hearn, D., and Baker, M. P. 1997. Computer graphics (2nd ed.): C version. Prentice-Hall, Inc., Upper Saddle River, NJ, USA.
[4]
Rath, J., 2009. The data-crunching powerhouse behind 'avatar'. http://www.datacenterknowledge.com/archives/2009/12/22/the-data-crunching-power, December.

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  • (2020)Classification and Comparison of Cloud Renderfarm Services for Recommender SystemsInnovative Data Communication Technologies and Application10.1007/978-3-030-38040-3_5(45-56)Online publication date: 31-Jan-2020
  • (2019)Improving the Performance of Inter-node Data Exchange in Cloud-based Distributed Ray Tracing by CompressionProceedings of the 3rd International Conference on Video and Image Processing10.1145/3376067.3376108(195-200)Online publication date: 20-Dec-2019
  • (2017)PGE Production in Southern Africa, Part II: Environmental AspectsMinerals10.3390/min71102257:11(225)Online publication date: 18-Nov-2017
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      cover image ACM Conferences
      SIGGRAPH '11: ACM SIGGRAPH 2011 Posters
      August 2011
      92 pages
      ISBN:9781450309714
      DOI:10.1145/2037715
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      Published: 07 August 2011

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      View all
      • (2020)Classification and Comparison of Cloud Renderfarm Services for Recommender SystemsInnovative Data Communication Technologies and Application10.1007/978-3-030-38040-3_5(45-56)Online publication date: 31-Jan-2020
      • (2019)Improving the Performance of Inter-node Data Exchange in Cloud-based Distributed Ray Tracing by CompressionProceedings of the 3rd International Conference on Video and Image Processing10.1145/3376067.3376108(195-200)Online publication date: 20-Dec-2019
      • (2017)PGE Production in Southern Africa, Part II: Environmental AspectsMinerals10.3390/min71102257:11(225)Online publication date: 18-Nov-2017
      • (2015)Ray tracing within a data parallel framework2015 IEEE Pacific Visualization Symposium (PacificVis)10.1109/PACIFICVIS.2015.7156388(279-286)Online publication date: Apr-2015
      • (2012)Platinum Availability for Future Automotive TechnologiesEnvironmental Science & Technology10.1021/es301110e46:23(12986-12993)Online publication date: 19-Nov-2012
      • (2011)Investigation of the potential for mineral carbonation of PGM tailings in South AfricaMinerals Engineering10.1016/j.mineng.2011.07.00524:12(1348-1356)Online publication date: Oct-2011

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