{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/somoclu-an-efficient-parallel-library-for","title":"Somoclu: An Efficient Parallel Library for Self-Organizing Maps","arxiv_id":"1305.1422","date":"2013-05-07","proceeding":null,"authors":["Peter Wittek","Shi Chao Gao","Ik Soo Lim","Li Zhao"],"abstract":"Somoclu is a massively parallel tool for training self-organizing maps on\nlarge data sets written in C++. It builds on OpenMP for multicore execution,\nand on MPI for distributing the workload across the nodes in a cluster. It is\nalso able to boost training by using CUDA if graphics processing units are\navailable. A sparse kernel is included, which is useful for high-dimensional\nbut sparse data, such as the vector spaces common in text mining workflows.\nPython, R and MATLAB interfaces facilitate interactive use. Apart from fast\nexecution, memory use is highly optimized, enabling training large emergent\nmaps even on a single computer.","url_abs":"http://arxiv.org/abs/1305.1422v4","url_pdf":"http://arxiv.org/pdf/1305.1422v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"somoclu-an-efficient-parallel-library-for","repo_url":"https://github.com/Cognitana-Research/NNOHD","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"somoclu-an-efficient-parallel-library-for","repo_url":"https://github.com/UnofficialJuliaMirror/Somoclu.jl-b42f4170-51a6-56fa-baee-02fb57ff6893","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"somoclu-an-efficient-parallel-library-for","repo_url":"https://github.com/UnofficialJuliaMirrorSnapshots/Somoclu.jl-b42f4170-51a6-56fa-baee-02fb57ff6893","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"somoclu-an-efficient-parallel-library-for","repo_url":"https://github.com/peterwittek/somoclu","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}