A perceptually-driven parallel algorithm for efficient radiosity simulation

The authors describe a novel algorithm for computing view-independent finite element radiosity solutions on distributed shared memory parallel architectures. Our approach is based on the notion of a subiteration 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 subiterations, we show how radiosity solutions can be generated without the need for processor synchronization between iterations of the progressive refinement algorithm. The only significant source of interprocessor communication required by our method is for visibility calculations. We also describe a perceptually driven approach to visibility estimation, which employs an efficient volumetric grid structure and attempts to reduce the amount of interprocessor communication by approximating visibility queries between distant patches. Our algorithm also eliminates the need for dynamic load balancing until the end of the solution process and is shown to achieve a superlinear speedup in many situations.