分布式内存机的并行细化

J. Baek, K. Teague
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引用次数: 1

摘要

在本文中,我们提出了一种基于边界的模糊模糊算法。提取每个目标区域的边界,并将其链接到每个目标区域。将得到的对象边界数据根据对象的大小和负载均衡的节点数进行划分,然后将被划分的对象划分到节点上。节点中的每个边界i都投影在一个工作平面上。接下来,边界数据被反复压缩,直到只剩下区域的骨架。传统算法和新算法都是在超立方体拓扑的多处理器计算机iPSC/2上实现的。对两种算法进行了比较和分析。给出了一些结果图和执行时间。
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Parallel Thinning on a Distributed Memory Machine
A p a r a l l e l th inning algor i thm based on boundary fo l lowing i s presented i n t h i s paper. The boundary o f each object region i s extracted and l inked i n pa ra l l e l . The resu l t ing object boundary data i s div ided based on the object s ize and the nurrber o f nodes f o r load balancing, then the divided objects are red is t r ibu ted t o the nodes. Each boundary i n a node i s projected on a Ilworking planell. Next, the boundary data i s repeatedly shrunken unti l only the skeleton o f the region remains. The conventional i t e r a t i v e pa ra l l e l algori thm as wel l as our new algor i thm are implemented on a hypercubetopology multiprocessor computer, the I n t e l iPSC/2. The two algorithms are compared and analyzed. Some resu l t ing f igures and execution times are presented.
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