Pixel-planes 5: a heterogeneous multiprocessor graphics system using processor-enhanced memories
SIGGRAPH '89 Proceedings of the 16th annual conference on Computer graphics and interactive techniques
An introduction to ray tracing
An introduction to ray tracing
Using MPI: portable parallel programming with the message-passing interface
Using MPI: portable parallel programming with the message-passing interface
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
Generating computer animations with frame coherence in a distributed computing environment
ACM-SE 36 Proceedings of the 36th annual Southeast regional conference
A Characterization of Ten Hidden-Surface Algorithms
ACM Computing Surveys (CSUR)
COMPCON '96 Proceedings of the 41st IEEE International Computer Conference
Exploiting Frame to Frame Coherence in a Virtual Reality System
VRAIS '96 Proceedings of the 1996 Virtual Reality Annual International Symposium (VRAIS 96)
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Rendering high-quality computer animations requires intensive computation, and therefore a large amount of time. One way to speed up this process is to devise rendering algorithms which reduce computation by taking advantage of image characteristics, such as frame or temporal coherence. Another way is to run the rendering process on specialized or enhanced hardware, such as a multiprocessor machine. This paper details our experiences in combining these techniques through a parallel rendering algorithm exploiting frame coherence run on a network of workstations acting as a single processing system. This system provides a powerjful and general method for obtaining high-quality animations with a significant reduction in computation and overall processing time. We present several techniques for partitioning the data across the workstation processors and report our results for each. While all of the partitioning schemes are scalable, some handle load balancing more effectively than others.