@phdthesis{1999-reinhard-0,
  title={Scheduling and Data Management for Parallel Ray Tracing},
  author={Erik Reinhard},
  school={Department of Computer Science, University of Bristol},
  bpages={133},
  rpages={11},
  month={October},
  year={1999},
  keywords={Graphics,Parallel_Processing},
  abstract={Parallelising ray tracing with a data parallel approach
allows rendering of arbitrarily large models, but the inherent load
imbalances may lead to severe inefficiencies. To compensate for the
uneven load distribution, demand-driven tasks may be split off and
scheduled to processors that are less busy. We propose a hybrid scheduling
algorithm which brings tasks and data together according to coherence
between rays. Coherent tasks are scheduled demand driven and the remainder
is executed data parallel. This method removes the worst hot-spots
from the data parallel component and reschedules those as demand driven
tasks, thereby evening out the workload. 

Processing power, communication and memory are three resources which
should be evenly used. Our current implementation is assessed against
these requirements. Related issues, such as the distribution of the
workload over space and the resulting requirements for the distribution
objects over the processors, are investigated as well. 

Finally, an assessment is made of the algorithm's ability to deal with
complexity in the form of large amounts of geometry and difficult lighting
conditions in the form of diffuse inter-reflection calculations.},
  source={tech-reports/1999/1999-reinhard-0.pdf},
  pubtype={17}
}