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Embed. Comput. Syst."],"published-print":{"date-parts":[[2019,10,31]]},"abstract":"<jats:p>\n            As modern embedded systems like cars need high-power integrated CPUs--GPU SoCs for various real-time applications such as lane or pedestrian detection, they face greater thermal problems than before, which may, in turn, incur higher failure rate and cooling cost. We demonstrate, via experimentation on a representative CPUs--GPU platform, the importance of accounting for two distinct thermal characteristics\u2014the\n            <jats:italic>platform\u2019s temperature imbalance<\/jats:italic>\n            and\n            <jats:italic>different power dissipations of different tasks<\/jats:italic>\n            \u2014in real-time scheduling to avoid any burst of power dissipations while guaranteeing all timing constraints. To achieve this goal, we propose a new\n            <jats:italic>&lt;u&gt;R&lt;\/u&gt;eal-&lt;u&gt;T&lt;\/u&gt;ime &lt;u&gt;T&lt;\/u&gt;hermal-&lt;u&gt;A&lt;\/u&gt;ware &lt;u&gt;S&lt;\/u&gt;cheduling<\/jats:italic>\n            (RT-TAS) framework. We first capture different CPU cores\u2019 temperatures caused by different GPU power dissipations (i.e.,\n            <jats:italic>CPUs--GPU thermal coupling<\/jats:italic>\n            ) with core-specific thermal coupling coefficients. We then develop\n            <jats:italic>thermally-balanced<\/jats:italic>\n            task-to-core assignment and\n            <jats:italic>CPUs--GPU co-scheduling<\/jats:italic>\n            . The former addresses the platform\u2019s temperature imbalance by efficiently distributing the thermal load across cores while preserving scheduling feasibility. Building on the thermally-balanced task assignment, the latter\n            <jats:italic>cooperatively<\/jats:italic>\n            schedules CPU and GPU computations to avoid simultaneous peak power dissipations on both CPUs and GPU, thus mitigating excessive temperature rises while meeting task deadlines. We have implemented and evaluated RT-TAS on an automotive embedded platform to demonstrate its effectiveness in reducing the maximum temperature by 6\u221212.2\u00b0\n            <jats:italic>C<\/jats:italic>\n            over existing approaches without violating any task deadline.\n          <\/jats:p>","DOI":"10.1145\/3358235","type":"journal-article","created":{"date-parts":[[2019,10,10]],"date-time":"2019-10-10T13:13:05Z","timestamp":1570713185000},"page":"1-25","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":34,"title":["Thermal-Aware Scheduling for Integrated CPUs--GPU Platforms"],"prefix":"10.1145","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6393-2994","authenticated-orcid":false,"given":"Youngmoon","family":"Lee","sequence":"first","affiliation":[{"name":"University of Michigan, Ann Arbor, MI"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0355-5784","authenticated-orcid":false,"given":"Kang G.","family":"Shin","sequence":"additional","affiliation":[{"name":"University of Michigan, Ann Arbor, MI"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0355-5784","authenticated-orcid":false,"given":"Hoon Sung","family":"Chwa","sequence":"additional","affiliation":[{"name":"DGIST, Daegu, South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,10,8]]},"reference":[{"key":"e_1_2_1_2_1","volume-title":"On the design and application of thermal isolation servers. 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