ハシモト　マサトモ   Masatomo Hashimoto   橋本　政朋    所属   千葉工業大学  人工知能・ソフトウェア技術研究センター 人工知能・ソフトウェア技術研究センター    職種   主席研究員
言語種別	英語
発行・発表の年月	2015/05
形態種別	国際会議プロシーディングス
査読	査読あり
標題	Extracting Facts from Performance Tuning History of Scientific Applications for Predicting Effective Optimization Patterns
執筆形態	共著
掲載誌名	Proceedings of the 12th Working Conference on Mining Software Repositories
掲載区分	国外
出版社・発行元	IEEE
巻・号・頁	pp.13-23
著者・共著者	Masatomo Hashimoto, Masaaki Terai, Toshiyuki Maeda, Kazuo Minami
概要	In general, performance tuning is conducted as transient tasks without version control systems. Tuning histories may lack explicit facts about what kind of program transformation contributed to the better performance or even about the chronological order of the source code snapshots. For reconstructing the missing information, we employ a state-of-the-art fine-grained change pattern identification tool for inferring applied transformation patterns only from an unordered set of source code snapshots. The extracted facts are intended to be stored and queried for further data mining. This paper reports on experiments of tuning pattern identification followed by predictive model construction conducted for a few scientific applications tuned for the K supercomputer.
DOI	10.1109/MSR.2015.9
ISBN	978-0-7695-5594-2
researchmap用URL	https://ieeexplore.ieee.org/document/7180063