Synopsis
Learn powerful, parallel techniques to solve complex problems faster, with clear, general methods you can apply across geometry and data structures. This book presents a practical framework for solving large problems in parallel by adapting the divide-and-conquer approach. It focuses on how to organize work, manage complex merges, and maintain efficiency across multiple processors, with many concrete techniques you can transfer to real-world challenges. The discussion centers on geometric problems, but the methods generalize to a wide range of tasks in computer science.
- General techniques for parallel divide-and-conquer and cascading merges
- How to handle partial orders and maintain efficient, sortable structures in parallel
- Applications to trapezoidal decomposition, planar point location, and segment intersection
- Optimization results that achieve time and processor bounds close to theoretical limits
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