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Cost-based workload balancing for ray tracing on multi-GPU systems

Published:21 July 2013Publication History

ABSTRACT

Ray tracing is at the core of most techniques for creating realistic imagery. Parallel implementations of ray tracing handle the irregular workload through task systems. The strengths of static and dynamic scheduling strategies are complementary to each other. Static strategies do not incur in synchronization overhead while dynamic strategies generally provide computational times closer to the optimal scheduling. Hybrid strategies combining good static initialization and dynamic task assignation have been shown to be a better alternative than pure static and dynamic strategies [Heirich and Arvo 1998]. We experiment with a novel strategy for load balancing on multi-GPU systems. We obtain a quick estimate of the cost of traversing batches of rays over bounding volume hierarchies. The estimated costs are used to achieve a tighter assignation of tasks to processing units. Results suggest that cost-based initialization can enhance common balancing strategies and reduce rendering times.

References

  1. Aila, T., and Laine, S. 2009. Understanding the efficiency of ray traversal on GPUs. In Proc. High-Performance Graphics 2009, 145--149. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Heirich, A., and Arvo, J. 1998. A competitive analysis of load balancing strategies for parallel ray tracing. The Journal of Supercomputing 12, 1-2, 57--68. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Conferences
    SIGGRAPH '13: ACM SIGGRAPH 2013 Posters
    July 2013
    115 pages
    ISBN:9781450323420
    DOI:10.1145/2503385

    Copyright © 2013 ACM

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 21 July 2013

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