{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T23:02:35Z","timestamp":1777676555687,"version":"3.51.4"},"reference-count":26,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2015,3,16]],"date-time":"2015-03-16T00:00:00Z","timestamp":1426464000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["The International Journal of High Performance Computing Applications"],"published-print":{"date-parts":[[2015,8]]},"abstract":"<jats:p>Kernel density estimation (KDE) is a statistical technique used to estimate the probability density function of a sample set with unknown density function. It is considered a fundamental data-smoothing problem for use with large datasets, and is widely applied in areas such as climatology and biometry. Due to the large volumes of data that these problems usually process, KDE is a computationally challenging problem. Current HPC platforms with built-in accelerators have an enormous computing power, but they have to be programmed efficiently in order to take advantage of that power. We have developed a novel strategy to compute KDE using bounded kernels, trying to minimize memory accesses, and implemented it as a parallel program targeting multi-core and many-core processors. The efficiency of our code has been tested with different datasets, obtaining impressive levels of acceleration when taking as reference alternative, state-of-the-art KDE implementations.<\/jats:p>","DOI":"10.1177\/1094342015576813","type":"journal-article","created":{"date-parts":[[2015,3,16]],"date-time":"2015-03-16T22:39:13Z","timestamp":1426545553000},"page":"331-347","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":9,"title":["An efficient implementation of kernel density estimation for multi-core and many-core architectures"],"prefix":"10.1177","volume":"29","author":[{"given":"Unai","family":"Lopez-Novoa","sequence":"first","affiliation":[{"name":"Department of Computer Architecture and Technology, University of the Basque Country UPV\/EHU, Donostia-San Sebastian, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jon","family":"S\u00e1enz","sequence":"additional","affiliation":[{"name":"Department of Applied Physics II, University of the Basque Country UPV\/EHU, Leioa, Spain"},{"name":"Plentzia Itsas Estazioa, University of the Basque Country UPV\/EHU, Plentzia, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander","family":"Mendiburu","sequence":"additional","affiliation":[{"name":"Department of Computer Architecture and Technology, University of the Basque Country UPV\/EHU, Donostia-San Sebastian, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose","family":"Miguel-Alonso","sequence":"additional","affiliation":[{"name":"Department of Computer Architecture and Technology, University of the Basque Country UPV\/EHU, Donostia-San Sebastian, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2015,3,16]]},"reference":[{"key":"bibr1-1094342015576813","volume-title":"Non-Parametric Econometrics","author":"Ahamada I","year":"2010"},{"key":"bibr2-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1016\/S0168-1923(00)00240-9"},{"key":"bibr3-1094342015576813","unstructured":"Bosman PA, Thierens D (2000) Ideas based on the normal kernels probability density function. Technical Report 11, Department of Computer Science, Utrecht University, The Netherlands."},{"key":"bibr4-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1038\/19745"},{"key":"bibr5-1094342015576813","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v021.i07"},{"key":"bibr6-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2003.1240123"},{"key":"bibr7-1094342015576813","volume-title":"Introduction to Statistical Pattern Recognition","author":"Fukunaga K","year":"1990"},{"key":"bibr8-1094342015576813","volume-title":"Computational Statistics","author":"Givens G","year":"2005"},{"key":"bibr9-1094342015576813","volume-title":"Intel Xeon Phi Coprocessor High Performance Programming","author":"Jeffers J","year":"2013"},{"key":"bibr10-1094342015576813","first-page":"1","volume":"32","author":"Leyk Z","year":"1994","journal-title":"Proceedings of the CMA"},{"key":"bibr11-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2014.2308216"},{"key":"bibr12-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72588-6_120"},{"key":"bibr13-1094342015576813","first-page":"1526","volume-title":"7th asian control conference (ASCC 2009)","author":"Luo N","year":"2009"},{"key":"bibr14-1094342015576813","doi-asserted-by":"publisher","DOI":"10.12988\/ams.2013.13133"},{"key":"bibr15-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1109\/MCSE.2011.36"},{"key":"bibr16-1094342015576813","unstructured":"OpenACC (2013) The OpenACC Application Programming Interface. Technical Report 2.0a, OpenACC.org."},{"key":"bibr17-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1175\/JCLI4253.1"},{"key":"bibr18-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(01)00109-8"},{"key":"bibr19-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1038\/nature10242"},{"key":"bibr20-1094342015576813","volume-title":"Multivariate Density Estimation: Theory, Practice, and Visualization","author":"Scott DW","year":"2009"},{"key":"bibr21-1094342015576813","doi-asserted-by":"publisher","DOI":"10.25080\/Majora-92bf1922-011"},{"key":"bibr22-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1214\/088342304000000297"},{"key":"bibr23-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-3324-9"},{"key":"bibr24-1094342015576813","volume-title":"workshop on high performance analytics - algorithms, implementations, and applications","author":"Srinivasan BV","year":"2010"},{"key":"bibr25-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-21706-2"},{"key":"bibr26-1094342015576813","doi-asserted-by":"publisher","DOI":"10.1080\/10485250500304849"}],"container-title":["The International Journal of High Performance Computing Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1094342015576813","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/1094342015576813","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/1094342015576813","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T08:19:24Z","timestamp":1777450764000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/1094342015576813"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,3,16]]},"references-count":26,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2015,8]]}},"alternative-id":["10.1177\/1094342015576813"],"URL":"https:\/\/doi.org\/10.1177\/1094342015576813","relation":{},"ISSN":["1094-3420","1741-2846"],"issn-type":[{"value":"1094-3420","type":"print"},{"value":"1741-2846","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,3,16]]}}}