Volume Rendering on Scalable Shared-Memory MIMD Architectures

Jason Nieh, Marc Levoy

Proceedings of the 1992 Workshop on Volume Visualization, ed. A. Kaufman and W. Lorensen, ACM, Boston, MA, October 19-20, 1992, pp. 17-24. (Figure)

Abstract

Volume rendering is a useful visualization technique for under- standing the large amounts of data generated in a variety of scien- tific disciplines. Routine use of this technique is currently limited by its computational expense. We have designed a parallel volume rendering algorithm for MIMD architectures based on ray tracing and a novel task queue image partitioning technique. The combi- nation of ray tracing and MIMD architectures allows us to employ algorithmic optimizations such as hierarchical opacity enumera- tion, early ray termination, and adaptive image sampling. The use of task queue image partitioning makes these optimizations effi- cient in a parallel framework. We have implemented our algorithm on the Stanford DASH Multiprocessor, a scalable shared-memory MIMD machine. Its single address-space and coherent caches pro- vide programming ease and good performance for our algorithm. With only a few days of programming effort, we have obtained nearly linear speedups and near real-time frame update rates on a 48 processor machine. Since DASH is constructed from Silicon Graphics multiprocessors, our code runs on any Silicon Graphics workstation without modification.

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Columbia University Department of Computer Science