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These approaches provide per-workload analysis but do not provide a holistic understanding of the utilization and effectiveness of caches under the ever-growing contention that comes standard with scaling cores. We present Contention Analysis in Shared Hierarchies using Thefts, or CASHT,\n            <jats:xref ref-type=\"fn\">\n              <jats:sup>1<\/jats:sup>\n            <\/jats:xref>\n            a framework for capturing cache contention information both offline and online. CASHT takes advantage of cache statistics made richer by observing a consequence of cache contention: inter-core evictions, or what we call THEFTS. We use thefts to complement more familiar cache statistics to train a learning model based on Gradient-boosting Trees (GBT) to predict the best ways to partition the last-level cache. GBT achieves 90+% accuracy with trained models as small as 100 B and at least 95% accuracy at 1 kB model size when predicting the best way to partition two workloads. CASHT employs a novel run-time framework for collecting thefts-based metrics despite partition intervention, and enables per-access sampling rather than set sampling that could add overhead but may not capture true workload behavior. Coupling CASHT and GBT for use as a dynamic policy results in a very lightweight and dynamic partitioning scheme that performs within a margin of error of Utility-based Cache Partitioning at a 1\/8 the overhead.\n          <\/jats:p>","DOI":"10.1145\/3494538","type":"journal-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T05:49:00Z","timestamp":1643003340000},"page":"1-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["CASHT: Contention Analysis in Shared Hierarchies with Thefts"],"prefix":"10.1145","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9207-4864","authenticated-orcid":false,"given":"Cesar","family":"Gomes","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maziar","family":"Amiraski","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Hempstead","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Tufts University, Medford, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,1,23]]},"reference":[{"key":"e_1_3_2_2_2","article-title":"Cache Replacement Championship 2","author":"Texas A&M.","year":"2017","unstructured":"Texas A&M. 2017. 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