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Somoclu: An efficient parallel library for self-organizing maps
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نویسنده
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wittek p. ,gao s.c. ,lim i.s. ,zhao l.
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منبع
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journal of statistical software - 2017 - دوره : 78 - شماره : 0
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چکیده
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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. © 2017,american statistical association. all rights reserved.
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کلیدواژه
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C++; CUDA; Distributed computing; ESOM; GPU; MATLAB; Multicore; Parallel computing; Python; R; SOM
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آدرس
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swedish school of library and information science,university of borås,borås,50190,sweden,icfo – the institute of photonic sciences,the barcelona institute of science and technology,castelldefels,barcelona,08860, Spain, future information technology,research institute of information technology,tsinghua university,beijing,100084, China, school of computer science,bangor university,bangor,ll57 1ut, United Kingdom, future information technology,research institute of information technology,tsinghua university,beijing,100084, China
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Authors
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