{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T05:12:21Z","timestamp":1783746741992,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":47,"publisher":"ACM","license":[{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001459","name":"Ministry of Education - Singapore","doi-asserted-by":"publisher","award":["Academic Research Fund Tier 1 (FY2021)"],"award-info":[{"award-number":["Academic Research Fund Tier 1 (FY2021)"]}],"id":[{"id":"10.13039\/501100001459","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,7,13]]},"DOI":"10.1145\/3806645.3807592","type":"proceedings-article","created":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T04:21:11Z","timestamp":1783743671000},"page":"361-373","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["CARBS: Compiler Autotuning via Randomized Biased Search"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9763-3319","authenticated-orcid":false,"given":"Wei","family":"Li","sequence":"first","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5009-3514","authenticated-orcid":false,"given":"Bin","family":"Gao","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4281-2053","authenticated-orcid":false,"given":"Weng-Fai","family":"Wong","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"key":"e_1_3_3_1_2_2","doi-asserted-by":"crossref","unstructured":"Lelac Almagor Keith\u00a0D Cooper Alexander Grosul Timothy\u00a0J Harvey Steven\u00a0W Reeves Devika Subramanian Linda Torczon and Todd Waterman. 2004. Finding effective compilation sequences. ACM SIGPLAN Notices 39 7 (2004) 231\u2013239.","DOI":"10.1145\/998300.997196"},{"key":"e_1_3_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/2628071.2628092"},{"key":"e_1_3_3_1_4_2","doi-asserted-by":"crossref","unstructured":"Amir\u00a0H Ashouri William Killian John Cavazos Gianluca Palermo and Cristina Silvano. 2018. A survey on compiler autotuning using machine learning. ACM Computing Surveys (CSUR) 51 5 (2018) 1\u201342.","DOI":"10.1145\/3197978"},{"key":"e_1_3_3_1_5_2","doi-asserted-by":"crossref","unstructured":"Prasanna Balaprakash Jack Dongarra Todd Gamblin Mary Hall Jeffrey\u00a0K Hollingsworth Boyana Norris and Richard Vuduc. 2018. Autotuning in high-performance computing applications. Proc. IEEE 106 11 (2018) 2068\u20132083.","DOI":"10.1109\/JPROC.2018.2841200"},{"key":"e_1_3_3_1_6_2","volume-title":"Workshop on profile and feedback-directed compilation","author":"Bodin Fran\u00e7ois","year":"1998","unstructured":"Fran\u00e7ois Bodin, Toru Kisuki, Peter Knijnenburg, Mike O\u2019Boyle, and Erven Rohou. 1998. Iterative compilation in a non-linear optimisation space. In Workshop on profile and feedback-directed compilation."},{"key":"e_1_3_3_1_7_2","doi-asserted-by":"crossref","unstructured":"CGE Boender. 1991. Bayesian Approach to Global Optimization\u2013Theory and Applications.","DOI":"10.2307\/2008419"},{"key":"e_1_3_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/IMSCCS.2006.11"},{"key":"e_1_3_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE43902.2021.00110"},{"key":"e_1_3_3_1_10_2","doi-asserted-by":"crossref","unstructured":"Yang Chen Shuangde Fang Yuanjie Huang Lieven Eeckhout Grigori Fursin Olivier Temam and Chengyong Wu. 2012. Deconstructing iterative optimization. ACM Transactions on Architecture and Code Optimization (TACO) 9 3 (2012) 1\u201330.","DOI":"10.1145\/2355585.2355594"},{"key":"e_1_3_3_1_11_2","doi-asserted-by":"crossref","unstructured":"Keith\u00a0D. Cooper Philip\u00a0J. Schielke and Devika Subramanian. 1999. Optimizing for reduced code space using genetic algorithms. languages compilers and tools for embedded systems (1999).","DOI":"10.1145\/314403.314414"},{"key":"e_1_3_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/CGO53902.2022.9741258"},{"key":"e_1_3_3_1_13_2","unstructured":"Free Software Foundation. 2010. GCC 4.5.0 Manual: Options That Control Optimization. https:\/\/gcc.gnu.org\/onlinedocs\/gcc-4.5.0\/gcc\/Optimize-Options.html."},{"key":"e_1_3_3_1_14_2","unstructured":"Free Software Foundation. 2023. GCC 13.2.0 Manual: Options That Control Optimization. https:\/\/gcc.gnu.org\/onlinedocs\/gcc-13.2.0\/gcc\/Optimize-Options.html."},{"key":"e_1_3_3_1_15_2","doi-asserted-by":"crossref","unstructured":"Grigori Fursin Yuriy Kashnikov Abdul\u00a0Wahid Memon Zbigniew Chamski Olivier Temam Mircea Namolaru Elad Yom-Tov Bilha Mendelson Ayal Zaks Eric Courtois et\u00a0al. 2011. Milepost GCC: Machine learning enabled self-tuning compiler. International Journal of Parallel Programming 39 3 (2011) 296\u2013327.","DOI":"10.1007\/s10766-010-0161-2"},{"key":"e_1_3_3_1_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/3735452.3735530"},{"key":"e_1_3_3_1_17_2","doi-asserted-by":"publisher","DOI":"10.1145\/2908961.2931696"},{"key":"e_1_3_3_1_18_2","volume-title":"10th International Workshop on Worst-Case Execution Time Analysis (WCET 2010)","author":"Gustafsson Jan","year":"2010","unstructured":"Jan Gustafsson, Adam Betts, Andreas Ermedahl, and Bj\u00f6rn Lisper. 2010. The M\u00e4lardalen WCET benchmarks: Past, present and future. In 10th International Workshop on Worst-Case Execution Time Analysis (WCET 2010). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik."},{"key":"e_1_3_3_1_19_2","doi-asserted-by":"publisher","DOI":"10.1109\/WWC.2001.990739"},{"key":"e_1_3_3_1_20_2","doi-asserted-by":"crossref","unstructured":"John\u00a0L Hennessy and David\u00a0A Patterson. 2019. A new golden age for computer architecture. Commun. ACM 62 2 (2019) 48\u201360.","DOI":"10.1145\/3282307"},{"key":"e_1_3_3_1_21_2","unstructured":"Jessica\u00a0R Jones. 2018. Auto-tuning Compiler Options for HPC. Ph.\u00a0D. Dissertation. University of Bath."},{"key":"e_1_3_3_1_22_2","unstructured":"Konstantinos Kanellis Cong Ding Brian Kroth Andreas M\u00fcller Carlo Curino and Shivaram Venkataraman. 2022. LlamaTune: Sample-efficient DBMS configuration tuning. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/2203.05128 (2022)."},{"key":"e_1_3_3_1_23_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1995.488968"},{"key":"e_1_3_3_1_24_2","doi-asserted-by":"publisher","DOI":"10.1109\/PACT.2000.888348"},{"key":"e_1_3_3_1_25_2","doi-asserted-by":"crossref","unstructured":"Peter\u00a0MW Knijnenburg Toru Kisuki and Michael\u00a0FP O\u2019Boyle. 2003. Combined selection of tile sizes and unroll factors using iterative compilation. The Journal of Supercomputing 24 (2003) 43\u201367.","DOI":"10.1023\/A:1020989410030"},{"key":"e_1_3_3_1_26_2","doi-asserted-by":"publisher","DOI":"10.1109\/FDL50818.2020.9232934"},{"key":"e_1_3_3_1_27_2","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1109\/MICRO.1997.645830","volume-title":"Proceedings of 30th Annual International Symposium on Microarchitecture","author":"Lee Chunho","year":"1997","unstructured":"Chunho Lee, Miodrag Potkonjak, and William\u00a0H Mangione-Smith. 1997. Mediabench: A tool for evaluating and synthesizing multimedia and communications systems. In Proceedings of 30th Annual International Symposium on Microarchitecture. IEEE, 330\u2013335."},{"key":"e_1_3_3_1_28_2","doi-asserted-by":"crossref","unstructured":"Charles\u00a0E Leiserson Neil\u00a0C Thompson Joel\u00a0S Emer Bradley\u00a0C Kuszmaul Butler\u00a0W Lampson Daniel Sanchez and Tao\u00a0B Schardl. 2020. There\u2019s plenty of room at the Top: What will drive computer performance after Moore\u2019s law? Science 368 6495 (2020) eaam9744.","DOI":"10.1126\/science.aam9744"},{"key":"e_1_3_3_1_29_2","unstructured":"Andy Liaw Matthew Wiener et\u00a0al. 2002. Classification and regression by randomForest. R news 2 3 (2002) 18\u201322."},{"key":"e_1_3_3_1_30_2","volume-title":"LivermoreC","unstructured":"LivermoreC. Year of Access. LivermoreC. https:\/\/www.netlib.org\/benchmark\/livermorec"},{"key":"e_1_3_3_1_31_2","doi-asserted-by":"publisher","DOI":"10.5555\/3049832.3049859"},{"key":"e_1_3_3_1_32_2","doi-asserted-by":"publisher","DOI":"10.1145\/3696443.3708961"},{"key":"e_1_3_3_1_33_2","first-page":"12\u2013pp","volume-title":"International Symposium on Code Generation and Optimization (CGO\u201906)","author":"Pan Zhelong","year":"2006","unstructured":"Zhelong Pan and Rudolf Eigenmann. 2006. Fast and effective orchestration of compiler optimizations for automatic performance tuning. In International Symposium on Code Generation and Optimization (CGO\u201906). IEEE, 12\u2013pp."},{"key":"e_1_3_3_1_34_2","doi-asserted-by":"publisher","DOI":"10.1109\/CGO53902.2022.9741263"},{"key":"e_1_3_3_1_35_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-78133-4_15"},{"key":"e_1_3_3_1_36_2","doi-asserted-by":"publisher","DOI":"10.1109\/MASCOT.2004.1348305"},{"key":"e_1_3_3_1_37_2","volume-title":"PolyBench","unstructured":"PolyBench. Year of Access. PolyBench. https:\/\/github.com\/ctuning\/ctuning-programs"},{"key":"e_1_3_3_1_38_2","unstructured":"Rodric\u00a0M Rabbah Ian Bratt Krste Asanovic and Anant Agarwal. 2004. Versatility and Versabench: A new metric and a benchmark suite for flexible architectures. (2004)."},{"key":"e_1_3_3_1_39_2","unstructured":"John Schulman Filip Wolski Prafulla Dhariwal Alec Radford and Oleg Klimov. 2017. Proximal policy optimization algorithms. arXiv preprint arXiv:https:\/\/arXiv.org\/abs\/1707.06347 (2017)."},{"key":"e_1_3_3_1_40_2","doi-asserted-by":"crossref","unstructured":"John Shalf. 2020. The future of computing beyond Moore\u2019s Law. Philosophical Transactions of the Royal Society A 378 2166 (2020) 20190061.","DOI":"10.1098\/rsta.2019.0061"},{"key":"e_1_3_3_1_41_2","volume-title":"SPEC CPU2017","author":"Corporation SPEC - Standard Performance Evaluation","unstructured":"SPEC - Standard Performance Evaluation Corporation. Year of Access. SPEC CPU2017. https:\/\/www.spec.org\/cpu2017\/"},{"key":"e_1_3_3_1_42_2","doi-asserted-by":"publisher","DOI":"10.1109\/INISTA52262.2021.9548573"},{"key":"e_1_3_3_1_43_2","doi-asserted-by":"crossref","unstructured":"Zheng Wang and Michael O\u2019Boyle. 2018. Machine learning in compiler optimization. Proc. IEEE 106 11 (2018) 1879\u20131901.","DOI":"10.1109\/JPROC.2018.2817118"},{"key":"e_1_3_3_1_44_2","doi-asserted-by":"crossref","first-page":"1059","DOI":"10.1109\/ICCCS52626.2021.9449274","volume-title":"2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS)","author":"Wei WU","year":"2021","unstructured":"WU Wei, ZHU Qi, et\u00a0al. 2021. Compiler Autotuning based on Hot Function for SHENWEI Processor. In 2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS). IEEE, 1059\u20131062."},{"key":"e_1_3_3_1_45_2","doi-asserted-by":"publisher","DOI":"10.1109\/CSCWD61410.2024.10580120"},{"key":"e_1_3_3_1_46_2","doi-asserted-by":"publisher","DOI":"10.1109\/ASE56229.2023.00209"},{"key":"e_1_3_3_1_47_2","doi-asserted-by":"crossref","unstructured":"Mingxuan Zhu Dan Hao and Junjie Chen. 2024. Compiler autotuning through multiple-phase learning. ACM Transactions on Software Engineering and Methodology 33 4 (2024) 1\u201338.","DOI":"10.1145\/3640330"},{"key":"e_1_3_3_1_48_2","doi-asserted-by":"crossref","unstructured":"Mingxuan Zhu Zeyu Sun and Dan Hao. 2025. PDCAT: Preference-Driven Compiler Auto-tuning. Proceedings of the ACM on Software Engineering 2 FSE (2025) 847\u2013867.","DOI":"10.1145\/3715756"}],"event":{"name":"HPDC '26: 35th International Symposium on High-Performance Parallel and Distributed Computing","location":"Cleveland USA","acronym":"HPDC '26","sponsor":["SIGHPC ACM Special Interest Group on High Performance Computing, Special Interest Group on High Performance Computing","SIGARCH ACM Special Interest Group on Computer Architecture"]},"container-title":["Proceedings of the 35th International Symposium on High-Performance Parallel and Distributed Computing"],"original-title":[],"deposited":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T04:23:49Z","timestamp":1783743829000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3806645.3807592"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,13]]},"references-count":47,"alternative-id":["10.1145\/3806645.3807592","10.1145\/3806645"],"URL":"https:\/\/doi.org\/10.1145\/3806645.3807592","relation":{},"subject":[],"published":{"date-parts":[[2026,7,13]]},"assertion":[{"value":"2026-07-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}