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Somoclu: An Efficient Parallel Library for Self-Organizing Maps

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Somoclu: An Efficient Parallel Library for Self-Organizing Maps. / Wittek, Peter; Gao, Shi Chao; Lim, Ik Soo et al.
Yn: Journal of Statistical Software, Cyfrol 78, Rhif 9, 09.06.2017, t. 1-21.

Allbwn ymchwil: Cyfraniad at gyfnodolyn › Erthygl › adolygiad gan gymheiriaid

HarvardHarvard

Wittek, P, Gao, SC, Lim, IS & Zhao, L 2017, 'Somoclu: An Efficient Parallel Library for Self-Organizing Maps', Journal of Statistical Software, cyfrol. 78, rhif 9, tt. 1-21. https://doi.org/10.18637/jss.v078.i09

APA

Wittek, P., Gao, S. C., Lim, I. S., & Zhao, L. (2017). Somoclu: An Efficient Parallel Library for Self-Organizing Maps. Journal of Statistical Software, 78(9), 1-21. https://doi.org/10.18637/jss.v078.i09

CBE

Wittek P, Gao SC, Lim IS, Zhao L. 2017. Somoclu: An Efficient Parallel Library for Self-Organizing Maps. Journal of Statistical Software. 78(9):1-21. https://doi.org/10.18637/jss.v078.i09

MLA

Wittek, Peter et al. "Somoclu: An Efficient Parallel Library for Self-Organizing Maps". Journal of Statistical Software. 2017, 78(9). 1-21. https://doi.org/10.18637/jss.v078.i09

VancouverVancouver

Wittek P, Gao SC, Lim IS, Zhao L. Somoclu: An Efficient Parallel Library for Self-Organizing Maps. Journal of Statistical Software. 2017 Meh 9;78(9):1-21. doi: 10.18637/jss.v078.i09

Author

Wittek, Peter ; Gao, Shi Chao ; Lim, Ik Soo et al. / Somoclu: An Efficient Parallel Library for Self-Organizing Maps. Yn: Journal of Statistical Software. 2017 ; Cyfrol 78, Rhif 9. tt. 1-21.

RIS

TY - JOUR

T1 - Somoclu: An Efficient Parallel Library for Self-Organizing Maps

AU - Wittek, Peter

AU - Gao, Shi Chao

AU - Lim, Ik Soo

AU - Zhao, Li

N1 - European Commission Seventh Frame-work Programme under Grant Agreement Number FP7-601138 PERICLES and by the AWS in Education Machine Learning Grant award

PY - 2017/6/9

Y1 - 2017/6/9

N2 - 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.

AB - 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.

UR - https://www.jstatsoft.org/index.php/jss/article/downloadSuppFile/v078i09/somoclu-1.7.4.tar.gz

U2 - 10.18637/jss.v078.i09

DO - 10.18637/jss.v078.i09

M3 - Article

VL - 78

SP - 1

EP - 21

JO - Journal of Statistical Software

JF - Journal of Statistical Software

SN - 1548-7660

IS - 9

ER -