Coarse-grained parallelism for hierarchical radiosity using group iterative methods

This paper describes algorithms that allow multiple hierarchical radiosity solvers to work on the same radiosity solution in parallel. We have developed a system based on a group iterative approach that repeatedly: 1) partitions patches into groups, 2) distributes a copy of each group to a slave processor which updates radiosities for all patches in that group, and 3) merges the updates back into a master solution. The primary advantage of this approach is that separate instantiations of a hierarchical radiosity solver can gather radiosity to patches in separate groups in parallel with very little contention or communication overhead. This feature, along with automatic partitioning and dynamic load balancing algorithms, enables our implemented system to achieve significant speedups running on moderate numbers of workstations connected by a local area network. This system has been used to compute the radiosity solution for a very large model representing a five floor building with furniture.