Simon Gibson.
Ph.D. Thesis, University of Manchester, September 1998.
The radiosity method is one of the most important global illumination algorithms, and the generation of geometrically complex, view-independent radiosity solutions has received much attention in recent years. This thesis provides two contributions that enable such radiosity solutions to be generated quickly and efficiently.
Firstly, a new framework for radiosity simulation (based on the progressive refinement method) is presented that uses perceptually-based calculations to control the simulation process. It is shown how such an approach enables computational effort to be focussed into those areas that have a visually significant effect on the appearance of the solution, leading to considerable savings in computation time.
Secondly, a novel algorithm for computing radiosity solutions on distributed shared-memory parallel architectures is described. Our approach is based on the notion of a {\it sub-iteration\/} being the transfer of energy from a single source to a subset of the scene's receiver patches. By using an efficient queue-based scheduling system to process these sub-iterations, we show how radiosity solutions can be generated without the need for processor synchronisation between iterations of the progressive refinement algorithm. This free-running method of computation exhibits excellent data locality, thereby limiting the amount of inter-processor communication that occurs, and eliminates the need for load-balancing until the end of the solution process. Results are presented indicating an almost linear speedup in the time required to generate a solution.
Awards: Best thesis, Department of Computer Science Research Student Symposium, University of Manchester, 1998-1999.