Parallel Algorithms for Image Analysis, Computational Geometry and Graphs

本研究包括设计、分析和 的有效算法和范例的实现， 解决图像分析、计算几何 和图论在并行计算机上的应用 算法将会 针对以下几类问题：（1）对于网孔： 计算几何，包括动态和静态 问题;（2）对于金字塔：限制图片， 由导出的度量定义;（3）对于树的网格， 超立方体：基本数据移动操作及其应用 图像分析、计算几何和图论; 此外，将开发一个映射， 算法，以有效地运行在一个网格的树;（4）为 具有可重构总线的网格：基本数据移动 操作，图像分析和图论;此外， 将提供演示，该模型结合了 （5）其他一些体系结构的优点;（5）对于 并行随机存取机：动态计算几何。 解决图像分析和计算问题的算法 几何将在超立方体多处理器上实现，其中 我们将专注于先进的数据简化技术， 数据减少时出现的负载平衡问题 执行。

This research consists of the design, analysis, and implementation of efficient algorithms and paradigms for the solution of problems in image analysis, computational geometry, and graph theory on parallel computers. The algorithms will be aimed at the following types of problems: (1) for the mesh: computational geometry, including dynamic as well as static problems; (2) for the pyramid: restricted pictures which are defined by derived metrics; (3) for the mesh-of-trees and hypercube: fundamental data-movement operations, with application to image analysis, computational geometry, and graph theory; also, a mapping will be developed that will allow pyramid algorithms to run efficiently on a mesh-of-trees; (4) for the mesh with a reconfigurable bus: fundamental data-movement operations, image analysis, and graph theory; also, a demonstration will be provided that this model combines the advantages of a number of other architectures; and (5) for the parallel random access machine: dynamic computational geometry. Algorithms to solve problems in image analysis and computational geometry will be implemented on a hypercube multiprocessor, where we will concentrate on advanced data reduction techniques and load-balancing issues that arise when data reduction is performed.