{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T15:33:26Z","timestamp":1759073606483,"version":"3.40.5"},"reference-count":14,"publisher":"Institute of Electronics, Information and Communications Engineers (IEICE)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEICE Trans. Inf. &amp; Syst."],"published-print":{"date-parts":[[2014]]},"DOI":"10.1587\/transinf.2014edp7190","type":"journal-article","created":{"date-parts":[[2014,11,30]],"date-time":"2014-11-30T23:30:16Z","timestamp":1417390216000},"page":"3124-3132","source":"Crossref","is-referenced-by-count":5,"title":["Predicting Vectorization Profitability Using Binary Classification"],"prefix":"10.1587","volume":"E97.D","author":[{"given":"Antoine","family":"TROUV\u00c9","sequence":"first","affiliation":[{"name":"Institute of Systems, Information Technologies and Nanotechnologies"}]},{"given":"Arnaldo J.","family":"CRUZ","sequence":"additional","affiliation":[{"name":"Engineering Department, Kyushu University"}]},{"given":"Dhouha","family":"BEN BRAHIM","sequence":"additional","affiliation":[{"name":"Computing Department, ENSEIRB-MATMECA"}]},{"given":"Hiroki","family":"FUKUYAMA","sequence":"additional","affiliation":[{"name":"Engineering Department, Kyushu University"}]},{"given":"Kazuaki J.","family":"MURAKAMI","sequence":"additional","affiliation":[{"name":"Engineering Department, Kyushu University"}]},{"given":"Hadrien","family":"CLARKE","sequence":"additional","affiliation":[{"name":"Engineering Department, Kyushu University"}]},{"given":"Masaki","family":"ARAI","sequence":"additional","affiliation":[{"name":"Fujitsu Laboratories Limited"}]},{"given":"Tadashi","family":"NAKAHIRA","sequence":"additional","affiliation":[{"name":"Fujitsu Laboratories Limited"}]},{"given":"Eiji","family":"YAMANAKA","sequence":"additional","affiliation":[{"name":"Fujitsu Limited"}]}],"member":"532","reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"[1] S. Kulkarni and J. Cavazos, \u201cMitigating the compiler optimization phase-ordering problem using machine learning,\u201d OOPSLA, pp.147-162, 2012.","DOI":"10.1145\/2398857.2384628"},{"key":"2","doi-asserted-by":"crossref","unstructured":"[2] E. Park, J. Cavazos, and M.A. Alvarez, \u201cUsing graph-based program characterization for predictive modeling,\u201d International Symposium on Code Generation and Optimization (CGO), pp.196-206, 2012.","DOI":"10.1145\/2259016.2259042"},{"key":"3","doi-asserted-by":"crossref","unstructured":"[3] K. Stock, L.N. Pouchet, and P. Sadayappan, \u201cUsing machine learning to improve automatic vectorization,\u201d ACM Transaction on Architecture and Code Optimization (TACO), vol.8, no.4, pp.1-23, 2012.","DOI":"10.1145\/2086696.2086729"},{"key":"4","doi-asserted-by":"crossref","unstructured":"[4] S. Maleki, G. Yaoqing, M.J. Garzaran, T. Wong, and D.A. Padua, \u201cAn evaluation of vectorizing compilers,\u201d Parallel Architecture and Compilation Techniques (PACT), pp.372-382, 2011.","DOI":"10.1109\/PACT.2011.68"},{"key":"5","doi-asserted-by":"crossref","unstructured":"[5] S. Kamil and A. Fox, \u201cBringing parallel performance to Python with domain-specific selective embedded just-in-time specialization,\u201d 10th Python for Scientific Computing Conference, 2011.","DOI":"10.25080\/Majora-ebaa42b7-00f"},{"key":"6","doi-asserted-by":"crossref","unstructured":"[6] G. Fursin, Y. Kashnikov, A.W. Memon, Z. Chamski, O. Temam, M. Namolaru, E. Yom-Tov, B. Mendelson, A. Zaks, E. Courtois, F. Bodin, P. Barnard, E. Ashton, E. Bonilla, J. Thomson, C.K.I. Williams, and M. O&apos;Boyle, \u201cMilepost GCC: Machine learning enabled self-tuning compiler,\u201d International Journal of Parallel Programming, vol.39, pp.296-327, 2011.","DOI":"10.1007\/s10766-010-0161-2"},{"key":"7","doi-asserted-by":"crossref","unstructured":"[7] L. Van Ertvelde and L. Eeckhout, \u201cBenchmark synthesis for architecture and compiler exploration,\u201d International Symposium on Workload Characterization, pp.1-11, 2010.","DOI":"10.1109\/IISWC.2010.5650208"},{"key":"8","doi-asserted-by":"crossref","unstructured":"[8] M.-W. Benabderrahmane, L.-N. Pouchet, and A. Cohen, \u201cThe polyhedral model is more widely applicable than you think,\u201d ETAPS International Conference on Compiler Construction (CC&apos;2010), pp.283-303, 2010.","DOI":"10.1007\/978-3-642-11970-5_16"},{"key":"9","doi-asserted-by":"crossref","unstructured":"[9] G, Pekhimenko and A.D. Brown, \u201cEfficient program compilation through machine learning techniques,\u201d International Workshop on Automatic Performance Tuning (iWAPT), Oct. 2009.","DOI":"10.1007\/978-1-4419-6935-4_19"},{"key":"10","doi-asserted-by":"crossref","unstructured":"[10] K. Hoste and L. Eeckhout, \u201cMicroarchitecture-independant workload characterization,\u201d MICRO, vol.27, no.3, pp.63-72, 2007.","DOI":"10.1109\/MM.2007.56"},{"key":"11","unstructured":"[11] C.M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006."},{"key":"12","doi-asserted-by":"crossref","unstructured":"[12] F. Agakov, E. Bonilla, J. Cavazos, B. Franke, G. Fursin, M.F.P. O&apos;Boyle, J. Thomson, M. Toussaint, and C.K.I. Williams, \u201cUsing machine learning to focus iterative optimization,\u201d International Symposium on Code Generation and Optimization (CGO), pp.295-305, March 2006.","DOI":"10.1109\/CGO.2006.37"},{"key":"13","doi-asserted-by":"crossref","unstructured":"[13] M. Stephenson and S. Amarasinghe, \u201cPredicting unroll factors using supervised classification,\u201d International symposium on code generation and optimization, pp.123-134, 2005.","DOI":"10.1109\/CGO.2005.29"},{"key":"14","unstructured":"[14] R. Allen and K. Kennedy, Optimizing Compilers for Modern Architectures, Morgan Kaufmann, 2002."}],"container-title":["IEICE Transactions on Information and Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E97.D\/12\/E97.D_2014EDP7190\/_pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,13]],"date-time":"2025-05-13T21:51:46Z","timestamp":1747173106000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.jstage.jst.go.jp\/article\/transinf\/E97.D\/12\/E97.D_2014EDP7190\/_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"references-count":14,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2014]]}},"URL":"https:\/\/doi.org\/10.1587\/transinf.2014edp7190","relation":{},"ISSN":["0916-8532","1745-1361"],"issn-type":[{"type":"print","value":"0916-8532"},{"type":"electronic","value":"1745-1361"}],"subject":[],"published":{"date-parts":[[2014]]}}}