Task Adaptive parallel graphics renderer.

摘要

This paper presents a graphics renderer which incorporates new partitioning methodologies of memory and work for efficient execution on a parallel computer. The Task Adaptive domain decomposition scheme is an image space method involving dynamic partitioning of rectangular pixel area tasks. The author shows that this method requires little overhead, allows coherence within a parallel context, handles worst case scenarios effectively, and executes efficiently with little processor synchronization necessary. Previous research in the area of memory and work decompositions for graphics rendering has been primarily limited to simulation studies and little practical experience. The algorithm presented here has been implemented on a scalable distributed memory multiprocessor and tested on a variety of input scenes. The author presents a theoretical and practical analysis in order to contrast its predicted and actual success. The implementation analysis indicates that load imbalance is the major cause of performance degradation at the higher processor counts. Even so, on a variety of test scenes, an average rendering speedup of 79 was achieved utilizing 96 processors on the BBN TC2000 multiprocessor with a processor efficiency range of 66% to 94%.