somoclu: An Efficient Parallel Library for Self-Organizing Maps

JOURNAL OF STATISTICAL SOFTWARE(2017)

引用 51|浏览25
暂无评分
摘要
somoclu is a massively parallel tool for training self-organizing maps on large data sets written in C++. It builds on OpenMP for multicore execution, and on MPI for distributing the workload across the nodes in a cluster. It is also able to boost training by using CUDA if graphics processing units are available. A sparse kernel is included, which is useful for high-dimensional but sparse data, such as the vector spaces common in text mining workflows. Python, R and MATLAB interfaces facilitate interactive use. Apart from fast execution, memory use is highly optimized, enabling training large emergent maps even on a single computer.
更多
查看译文
关键词
SOM,ESOM,distributed computing,parallel computing,multicore,GPU,C plus,CUDA,Python,R,MATLAB
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要