A scalable parallel ray tracing algorithm for satellite imagery

Ray-tracing, can produce high-quality images, however, the use of ray-tracing has been limited due to its high demands on computational power and memory bandwidth, especially in the case of satellite imagery. In this paper, we propose a scalable parallel ray tracing algorithm of satellite imagery on a cluster of multi-core architecture. The algorithm combines demand-driven and data-driven models in order to reduce communication on the cost of maintaining redundant data. In order to make the most of computer´s parallelism and increase computational efficiency, it combines two levels of parallelisms, the TLP parallelism brought by the many core architecture and the inter-node parallelism via MPI and OpenMP. Experiment results show that the algorithm is highly scalability.