A parallel implementation of the tree-structured self-organizing map

被引:0
|
作者
Lensu, A [1 ]
Koikkalainen, P [1 ]
机构
[1] Univ Jyvaskyla, Lab Data Anal, FIN-40351 Jyvaskyla, Finland
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This paper presents how Self-Organizing Maps (SOMs) can be trained efficiently using several, simultaneously executing threads on a shared memory Symmetric MultiProcessing (SMP) computer. The training method is a batch version of the Tree-Structured Self-Organizing Map. We note that SMP type of parallel training is very useful for large data sets obtained from nature, the process industry or large document collections, since we do not encounter similar model size limitations as with hardware SOM implementations.
引用
收藏
页码:370 / 379
页数:10
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