Data Movement Techniques for the Pyramid Computer

Abstract
The pyramid computer was initially proposed for performing high-speed low-level image processing. However, its regular geometry can be adapted naturally to many other problems, providing effective solutions to problems more complex than those previously considered. We illustrate this by presenting pyramid computer solutions to problems involving component labeling, minimal spanning forests, nearest neighbors, transitive closure, articulation points, bridge edges, etc. Central to these algorithms is our collection of data movement techniques which exploit the pyramid’s mix of tree and mesh connections. Our pyramid algorithms are significantly faster than their mesh-connected computer counterparts. For example, given a black/white square picture with n pixels, we can label the connected components in $\theta (n^{{1 / 4}} )$ time, as compared with the $\Omega (n^{{1 / 2}} )$ time required on the mesh-connected computer.

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