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Syst."],"published-print":{"date-parts":[[2025,5,31]]},"abstract":"<jats:p>\n            Run-time resource management (RTM) of multi-programmed workloads on heterogeneous multi-core platforms is challenging due to (i)\u00a0fixed power budget of the device, (ii)\u00a0variable performance requirements of the workloads, and (iii)\u00a0unknown arrival of the applications. Existing RTM solutions lack power-performance coordination, resulting in performance degradation during power actuation or power violations during performance provisioning. Exploiting inherent error-resilience of the applications can address the performance loss incurred in power actuation, by combining run-time approximation with traditional power knobs (including Dynamic Voltage\/Frequency Scaling, Task Migration, Degree of Parallelism, and\n            <jats:italic>CPU Quota<\/jats:italic>\n            ). In this work, we present an accuracy-aware resource management framework that jointly actuates run-time approximation and traditional power knobs for efficient power-performance management of multi-programmed and multi-threaded workloads running on heterogeneous mobile platforms. Our strategy configures the accuracy of the applications at run-time to exploit accuracy-performance trade-offs, by considering system-wide power-performance dynamics. We use heuristic estimation models to jointly enforce accuracy configuration and traditional power knobs settings at run-time. We evaluated our framework on real-world embedded mobile platforms, including Odroid XU3 and Asus Tinker Edge R boards to demonstrate the efficiency of our proposed approach across multiple workload scenarios. Our approach achieved 25% lower performance violations against the state-of-the-art run-time resource management policies at the cost of 2.2% accuracy loss across six applications.\n          <\/jats:p>","DOI":"10.1145\/3723357","type":"journal-article","created":{"date-parts":[[2025,3,13]],"date-time":"2025-03-13T10:48:33Z","timestamp":1741862913000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploiting Approximation for Run-time Resource Management of Embedded HMPs"],"prefix":"10.1145","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5298-6049","authenticated-orcid":false,"given":"Zain","family":"Taufique","sequence":"first","affiliation":[{"name":"Health Technology, University of Turku, Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3188-8703","authenticated-orcid":false,"given":"Anil","family":"Kanduri","sequence":"additional","affiliation":[{"name":"University of Turku, Turku, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3197-0723","authenticated-orcid":false,"given":"Antonio","family":"Miele","sequence":"additional","affiliation":[{"name":"DEIB, Politecnico di Milano, Milano, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0725-1155","authenticated-orcid":false,"given":"Amir","family":"Rahmani","sequence":"additional","affiliation":[{"name":"Computer Science, University of California, Irvine, California, United States and Institute of Computer Technology, Technische Universitat Wien, Wien, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5065-7906","authenticated-orcid":false,"suffix":"PhD","given":"Cristiana","family":"Bolchini","sequence":"additional","affiliation":[{"name":"Dip. 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