Efficient Parallel Radiosity for Terascale Applications

Riwei Wang, Hua Zhang, Yuefan Deng, Lei Ming

Abstract: Nowadays one of the most active areas of research in computer graphics is focused on improving the performance of radiosity methods for terascale visualization applications. The main problem for simulating large scenes based on radiosity algorithm is a highly time-consuming process. In this paper we present a task mapping model for achieving a good load balance on a distributed memory system. And we keep our focus on the solutions for massive data sets with complex geometric models. In order to evaluate the proposed method, a parallel radiosity algorithm was introduced to test our models on supercomputer simulator with cellular network. An efficient performance in terms of scalability and speedup has been obtained.