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High-level synthesis parameter tuning is a time-consuming process due to lengthy hardware compilation times\u2014synthesizing an FPGA design can take tens of hours. DSE helps find an optimal solution faster than brute-force methods without relying on designer intuition to achieve high-quality results. Sherlock is a DSE framework that can handle multiple conflicting optimization objectives and aggressively focuses on finding Pareto-optimal solutions. Sherlock integrates a model selection process to choose the regression model that helps reach the optimal solution faster. Sherlock designs a strategy based around the multi-armed bandit problem, opting to balance exploration and exploitation based on the learned and expected results. Sherlock can decrease the importance of models that do not provide correct estimates, reaching the optimal design faster. Sherlock is capable of tailoring its choice of regression models to the problem at hand, leading to a model that best reflects the application design space. We have tested the framework on a large dataset of FPGA design problems and found that Sherlock converges toward the set of optimal designs faster than similar frameworks.<\/jats:p>","DOI":"10.1145\/3511472","type":"journal-article","created":{"date-parts":[[2022,2,9]],"date-time":"2022-02-09T19:37:52Z","timestamp":1644435472000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":23,"title":["Sherlock: A Multi-Objective Design Space Exploration Framework"],"prefix":"10.1145","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9923-2554","authenticated-orcid":false,"given":"Quentin","family":"Gautier","sequence":"first","affiliation":[{"name":"University of California San Diego, La Jolla, CA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8355-6906","authenticated-orcid":false,"given":"Alric","family":"Althoff","sequence":"additional","affiliation":[{"name":"Tortuga Logic, San Jose, CA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2011-721X","authenticated-orcid":false,"given":"Christopher L.","family":"Crutchfield","sequence":"additional","affiliation":[{"name":"University of California San Diego, La Jolla, CA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9062-5570","authenticated-orcid":false,"given":"Ryan","family":"Kastner","sequence":"additional","affiliation":[{"name":"University of California San Diego, La Jolla, CA"}]}],"member":"320","published-online":{"date-parts":[[2022,3,8]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/2628071.2628092"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1145\/2967938.2967963"},{"key":"e_1_3_2_4_2","article-title":"Regret analysis of stochastic and nonstochastic multi-armed bandit problems","author":"Bubeck S\u00e9bastien","year":"2012","unstructured":"S\u00e9bastien Bubeck and Nicolo Cesa-Bianchi. 2012. 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