{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T14:31:18Z","timestamp":1781101878494,"version":"3.54.1"},"reference-count":29,"publisher":"IGI Global Scientific Publishing","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,1,1]]},"abstract":"<p>A ranking support vector machine (RSVM) is a typical pairwise method of learning to rank, which is effective in ranking problems. However, the training speed of RSVMs are not satisfactory, especially when solving large-scale data ranking problems. Recent years, many-core processing units (graphics processing unit (GPU), Many Integrated Core (MIC)) and multi-core processing units have exhibited huge superiority in the parallel computing domain. With the support of hardware, parallel programming develops rapidly. Open Computing Language (OpenCL) and Open Multi-Processing (OpenMP) are two of popular parallel programming interfaces. The authors present two high-performance parallel implementations of RSVM, an OpenCL version implemented on multi-core and many-core platforms, and an OpenMP version implemented on multi-core platform. The experimental results show that the OpenCL version parallel RSVM achieved considerable speedup on Intel MIC 7110P, NVIDIA Tesla K20M and Intel Xeon E5-2692v2, and it also shows good portability.<\/p>","DOI":"10.4018\/ijghpc.2019010102","type":"journal-article","created":{"date-parts":[[2018,10,8]],"date-time":"2018-10-08T13:25:20Z","timestamp":1539005120000},"page":"17-28","source":"Crossref","is-referenced-by-count":4,"title":["A High Performance Parallel Ranking SVM with OpenCL on Multi-core and Many-core Platforms"],"prefix":"10.4018","volume":"11","author":[{"given":"Huming","family":"Zhu","sequence":"first","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pei","family":"Li","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zheng","family":"Luo","sequence":"additional","affiliation":[{"name":"Xidian University, Xi'an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"key":"IJGHPC.2019010102-0","doi-asserted-by":"publisher","DOI":"10.1145\/1273496.1273513"},{"key":"IJGHPC.2019010102-1","doi-asserted-by":"crossref","unstructured":"Cao, Y. B., & Xu, J., L TY, Li H., Hon Y. & Hon HW. (2006). Adapting ranking SVM to document retrieval. In Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval (pp. 186-193). ACM.","DOI":"10.1145\/1148170.1148205"},{"issue":"6","key":"IJGHPC.2019010102-2","first-page":"933","article-title":"An efficient boosting algorithm for combining preferences.","volume":"4","author":"Y.Freund","year":"2003","journal-title":"Journal of Machine Learning Research"},{"key":"IJGHPC.2019010102-3","first-page":"1889","article-title":"Working set selection using second order information for training support vector machines.","volume":"6","author":"R. E.Fan","year":"2005","journal-title":"Journal of Machine Learning Research"},{"key":"IJGHPC.2019010102-4","first-page":"133","article-title":"Optimizing search engines using click through data.","author":"T.Joachims","year":"2002","journal-title":"Proceedings of the ACM Conference on Knowledge Discovery and Data Mining"},{"key":"IJGHPC.2019010102-5","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-012-1028-x"},{"key":"IJGHPC.2019010102-6","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-016-3244-2"},{"key":"IJGHPC.2019010102-7","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2012.06.012"},{"key":"IJGHPC.2019010102-8","first-page":"897","article-title":"McRank: Learning to rank using multiple classification and gradient boosting.","volume":"\u25aa\u25aa\u25aa","author":"P.Li","year":"2007","journal-title":"Advances in Neural Information Processing Systems"},{"key":"IJGHPC.2019010102-9","doi-asserted-by":"crossref","DOI":"10.1561\/9781601982452","article-title":"LETOR: Benchmark dataset for research on learning to rank for information retrieval.","author":"T. Y.Liu","year":"2007","journal-title":"Proceedings of SIGIR \u201907 Workshop on Learning to Rank for Information Retrieval."},{"key":"IJGHPC.2019010102-10","first-page":"775","article-title":"Metric Learning to Rank.","author":"B.McFee","year":"2010","journal-title":"Proceedings of the Twenty-seventh International Conference on Machine Learning"},{"key":"IJGHPC.2019010102-11","doi-asserted-by":"publisher","DOI":"10.1145\/1148170.1148246"},{"key":"IJGHPC.2019010102-12","doi-asserted-by":"crossref","unstructured":"Osuna, E., Freund, R., & Girosit, F. (1997, June). Training support vector machines: an application to face detection. In Proceedings, 1997 IEEE computer society conference on Computer vision and pattern recognition (pp. 130-136). IEEE.","DOI":"10.1109\/CVPR.1997.609310"},{"key":"IJGHPC.2019010102-13","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2010.12.005"},{"key":"IJGHPC.2019010102-14","first-page":"185","article-title":"Fast training of support vector machines using sequential minimal optimization.","author":"J.Platt","year":"1999","journal-title":"Advances in Kernel Methods-Support Vector Learning"},{"key":"IJGHPC.2019010102-15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2012.07.005"},{"key":"IJGHPC.2019010102-16","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2015.7351622"},{"key":"IJGHPC.2019010102-17","doi-asserted-by":"publisher","DOI":"10.1145\/1277741.1277809"},{"key":"IJGHPC.2019010102-18","doi-asserted-by":"publisher","DOI":"10.1109\/BigDataCongress.2015.16"},{"key":"IJGHPC.2019010102-19","doi-asserted-by":"publisher","DOI":"10.1109\/IPDPS.2014.88"},{"key":"IJGHPC.2019010102-20","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Sinclair, M., & Chien, A. A. (2013). Improving Performance Portability in OpenCL Programs. In Proceedings of28th International Supercomputing Conference, ISC 2013,LNCS (Vol. 7905, pp. 136-150).","DOI":"10.1007\/978-3-642-38750-0_11"},{"key":"IJGHPC.2019010102-21","doi-asserted-by":"publisher","DOI":"10.1504\/IJBDI.2016.077385"},{"key":"IJGHPC.2019010102-22","doi-asserted-by":"publisher","DOI":"10.1504\/IJBDI.2015.070596"},{"key":"IJGHPC.2019010102-23","doi-asserted-by":"publisher","DOI":"10.4018\/IJGHPC.2015040106"},{"key":"IJGHPC.2019010102-24","doi-asserted-by":"publisher","DOI":"10.4018\/ijghpc.2014010101"},{"key":"IJGHPC.2019010102-25","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.jpdc.2017.05.011","article-title":"An OpenCL framework for high performance extraction of image features.","volume":"109","author":"D. C.de Andrade","year":"2017","journal-title":"Journal of Parallel and Distributed Computing"},{"key":"IJGHPC.2019010102-26","doi-asserted-by":"publisher","DOI":"10.1016\/j.cpc.2017.03.013"},{"key":"IJGHPC.2019010102-27","first-page":"429","article-title":"Big Data Classification: A Combined Approach Based on Parallel and Approx SVM","volume":"2017","author":"W.Ksia\u00e2","year":"2017","journal-title":"Intelligent Interactive Multimedia Systems and Services"},{"issue":"4","key":"IJGHPC.2019010102-28","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1177\/1094342015580864","article-title":"Study of parallel programming models on computer clusters with Intel MIC coprocessors.","volume":"31","author":"M.Huang","year":"2017","journal-title":"International Journal of High Performance Computing Applications"}],"container-title":["International Journal of Grid and High Performance Computing"],"original-title":[],"language":"ng","link":[{"URL":"https:\/\/www.igi-global.com\/viewtitle.aspx?TitleId=216479","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T18:59:09Z","timestamp":1775242749000},"score":1,"resource":{"primary":{"URL":"https:\/\/services.igi-global.com\/resolvedoi\/resolve.aspx?doi=10.4018\/IJGHPC.2019010102"}},"subtitle":[""],"short-title":[],"issued":{"date-parts":[[2019,1,1]]},"references-count":29,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2019,1]]}},"URL":"https:\/\/doi.org\/10.4018\/ijghpc.2019010102","relation":{},"ISSN":["1938-0259","1938-0267"],"issn-type":[{"value":"1938-0259","type":"print"},{"value":"1938-0267","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,1,1]]}}}