Memory management for Union-Find algorithms
We provide a general tool to improve the real time performance of a broad class of Union-Find algorithms. This is done by minimizing the random access memory that is used and thus to avoid the well-known von Neumann bottleneck of synchronizing CPU and memory. A main application to image segmentation algorithms is demonstrated where the real time performance is drastically improved.
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