A Parallel Memory Efficient Framework for Out-of-Core Mesh Simplification

A general parallel framework is presented in this paper for simplification of very large mesh models. This framework is implemented on a dedicated cluster. To guarantee not to thrash the virtual memory system, load balancing is performed in this framework by providing an intelligent partitioning of the inputting model using a parallel global sorting. This partitioning ensures a near optimal utilization of the computational resources, and then ensures high quality output, low runtime and high parallel efficiency. To test the usability of this framework, we have implemented a parallel version of an improved vertex clustering simplification. A serial of experimental results have demonstrated that using this framework the parallel simplification is memory efficient and can handle extremely large data set as well as speed up the execution obviously.