Efficient Parallel Refinement for Hierarchical Radiosity on a DSM computer
Abstract
We introduce a simple, yet efficient extension to the hierarchical radiosity algorithm for the simulation of global illumination, taking advantage of a distributed shared memory (DSM) parallel architecture. Our task definition is based on a very fine grain decompo-sition of the refinement process at the level of individual pairs of hierarchical elements, therefore allowing a very simple implementation from an existing code with minimal mod-ifications. We describe a generic refinement scheme based on a scheduler, allowing both easy parallelization and reordering of refinement tasks, which is useful for interactive and user-driven applications. We show that a very simple task grouping mechanism suffices to avoid excessive time waste in synchronization. Results obtained on an SGI Origin computer with 64 processors validate the approach, with excellent speedups using the full capacity of the machine.
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