The computational demands of encoding and decoding motion-compensated transform representations of digital video are well-known, and even hard-wired solutions to single algorithms remain a design challenge. When interactivity or personalization are added, and when algorithms increase in complexity to include structured or object-based representations, not only do the requirements increase but so too does the need for computational flexibility. It is often proposed to solve the computational problem in a flexible manner by using multiple identical general-purpose processors in parallel (a multiple-instruction, multiple-data, or MIMD approach). Such methods, though, may not achieve the needed number of operations per second without large numbers of processors; in that case communications bottlenecks can arise and programmers can find difficulty in efficiently parallelizing software. A less-well-known form of parallel computation, based on streams, is conceptually closer to to the ways in...