Volume Rendering on Scalable Shared-Memory MIMD Architectures
Jason Nieh and
Proc. 1992 Workshop on Volume Visualization,
ed. A. Kaufman and W. Lorensen, ACM, Boston, Massachusetts,
October, 1992, pp. 17-24.
Volume rendering is a useful visualization technique for understanding the
large amounts of data generated in a variety of scientific 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 combination of ray tracing and MIMD architectures allows us to
employ algorithmic optimizations such as hierarchical opacity enumeration,
early ray termination, and adaptive image sampling. The use of task queue
image partitioning makes these optimizations efficient 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 provide 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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