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In this paper we give new techniques for designing efficient algorithms for computational geometry problems that are too large to be solved in internal memory. We use these techniques to develop optimal and practical algorithms for a number of important large-scale problems. We discuss our algorithms primarily in the context of single processor/single disk machines, a domain in which they are not only the first known optimal results but also of tremendous practical value. Our methods also produce the first known optimal algorithms for a wide range of two-level and hierarchical multilevel memory models, including parallel models. The algorithms are optimal both in terms of I/O cost and internal computation.>
Goodrich et al. (Mon,) studied this question.