{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T23:01:58Z","timestamp":1777676518945,"version":"3.51.4"},"reference-count":17,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2013,7,3]],"date-time":"2013-07-03T00:00:00Z","timestamp":1372809600000},"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":[[2013,11]]},"abstract":"<jats:p>Application auto-tuning has produced excellent results in a wide range of computing domains. Yet adapting an application to use this technology remains a predominately manual and labor intensive process. This paper explores first steps towards reducing adoption cost by focusing on two tasks: parameter identification and range selection. We show how these traditionally manual tasks can be automated in the context of Chapel, a parallel programming language developed by Cray Inc. Potential auto-tuning parameters may be inferred from existing Chapel applications by leveraging features unique to this language. After verification, these parameters may then be passed to an auto-tuner for an automatic search of the induced parameter space. To further automate adoption, we also present Tuna: an auto-tuning shell designed to tune applications by manipulating their command-line arguments. Finally, we demonstrate the immediate utility of this system by tuning two Chapel applications with little or no internal knowledge of the program source.<\/jats:p>","DOI":"10.1177\/1094342013493198","type":"journal-article","created":{"date-parts":[[2013,7,4]],"date-time":"2013-07-04T20:16:31Z","timestamp":1372968991000},"page":"394-402","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Towards fully automatic auto-tuning"],"prefix":"10.1177","volume":"27","author":[{"given":"Ray S","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey K","family":"Hollingsworth","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2013,7,3]]},"reference":[{"key":"bibr1-1094342013493198","doi-asserted-by":"publisher","DOI":"10.1145\/1687774.1687789"},{"key":"bibr2-1094342013493198","doi-asserted-by":"publisher","DOI":"10.1145\/1377596.1377597"},{"key":"bibr3-1094342013493198","doi-asserted-by":"publisher","DOI":"10.1109\/HIPS.2004.1299190"},{"key":"bibr4-1094342013493198","first-page":"36","volume-title":"Proceedings of the 13th IEEE international symposium on high performance distributed computing (HPDC \u201804)","author":"Chung IH","year":"2004"},{"key":"bibr5-1094342013493198","unstructured":"Free Software Foundation (2013) Optimize Options \u2013 Using the Gnu Compiler Collection (GCC). 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