{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T23:00:55Z","timestamp":1777676455766,"version":"3.51.4"},"reference-count":30,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2011,6,29]],"date-time":"2011-06-29T00:00:00Z","timestamp":1309305600000},"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":[[2011,8]]},"abstract":"<jats:p>In this paper, we take a concrete step towards materializing our long-term goal of providing a fully automatic end-to-end tuning infrastructure for arbitrary program components and full applications. We describe a general-purpose offline auto-tuning framework and apply it to an application benchmark, SMG2000, a semi-coarsening multigrid on structured grids. We show that the proposed system first extracts computationally intensive loop nests into separate executable functions, a code transformation called outlining. The outlined loop nests are then tuned by the framework and subsequently integrated back into the application. Each loop nest is optimized through a series of composable code transformations, with the transformations parameterized by unbound optimization parameters that are bound during the tuning process. The values for these parameters are selected using a search-based auto-tuner, which performs a parallel heuristic search for the best-performing optimized variants of the outlined loop nests. We show that our system pinpoints a code variant that performs 2.37 times faster than the original loop nest. When the full application is run using the code variant found by the system, the application\u2019s performance improves by 27%.<\/jats:p>","DOI":"10.1177\/1094342011414744","type":"journal-article","created":{"date-parts":[[2011,6,29]],"date-time":"2011-06-29T20:46:44Z","timestamp":1309380404000},"page":"286-294","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":26,"title":["Auto-tuning full applications: A case study"],"prefix":"10.1177","volume":"25","author":[{"given":"Ananta","family":"Tiwari","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Maryland, College Park, MD, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jeffrey K","family":"Hollingsworth","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Maryland, College Park, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Chun Chen","sequence":"additional","affiliation":[{"name":"School of Computing, University of Utah, Salt Lake City, UT, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mary","family":"Hall","sequence":"additional","affiliation":[{"name":"School of Computing, University of Utah, Salt Lake City, UT, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Chunhua Liao","sequence":"additional","affiliation":[{"name":"Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel J","family":"Quinlan","sequence":"additional","affiliation":[{"name":"Center for Applied Scientific Computing, Lawrence Livermore National Laboratory, Livermore, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacqueline","family":"Chame","sequence":"additional","affiliation":[{"name":"Information Sciences Institute, University of Southern California, Marina del Ray, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2011,6,29]]},"reference":[{"key":"atypb1","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1002\/cpe.1553","volume":"22","author":"Adhianto L.","journal-title":"Concurr Comput Pract Exper"},{"issue":"4","key":"atypb2","volume":"3","author":"Bailey DH","year":"2007","journal-title":"CTWatch Quarterly"},{"key":"atypb3","doi-asserted-by":"publisher","DOI":"10.1137\/S1064827598339141"},{"key":"atypb4","volume-title":"2010 IEEE International Symposium on Parallel Distributed Processing (IPDPS)","author":"Chandramowlishwaran A."},{"key":"atypb5","volume-title":"Model-Guided Empirical Optimization for Memory Hierarchy. 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