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A heterogeneous chiplet-based PIM architecture can harness the complementary strengths of these technologies to enable higher performance and energy efficiency. However, scheduling AI workloads across such a heterogeneous system is challenging due to competing performance objectives, dynamic workload characteristics, and power and thermal constraints. To address this need, we propose THERMOS, a thermally-aware, multi-objective scheduling framework for AI workloads on heterogeneous multi-chiplet PIM architectures. THERMOS trains a\n            <jats:italic toggle=\"yes\">single multi-objective reinforcement learning (MORL) policy<\/jats:italic>\n            that is capable of achieving Pareto-optimal execution time, energy, or a balanced objective at runtime, depending on the target preferences. Comprehensive evaluations show that THERMOS achieves up to 89% faster average execution time and 57% lower average energy consumption than baseline AI workload scheduling algorithms with only 0.14% runtime and 0.022% energy overhead.\n          <\/jats:p>","DOI":"10.1145\/3762655","type":"journal-article","created":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T11:51:43Z","timestamp":1755863503000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":8,"title":["THERMOS: Thermally-Aware Multi-Objective Scheduling of AI Workloads on Heterogeneous Multi-Chiplet PIM Architectures"],"prefix":"10.1145","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8585-9241","authenticated-orcid":false,"given":"Alish","family":"Kanani","sequence":"first","affiliation":[{"name":"University of Wisconsin-Madison","place":["Madison, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7905-9843","authenticated-orcid":false,"given":"Lukas","family":"Pfromm","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison","place":["Madison, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0334-4269","authenticated-orcid":false,"given":"Harsh","family":"Sharma","sequence":"additional","affiliation":[{"name":"Washington State University","place":["Pullman, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3848-5301","authenticated-orcid":false,"given":"Jana","family":"Doppa","sequence":"additional","affiliation":[{"name":"Washington State University","place":["Pullman, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5930-8531","authenticated-orcid":false,"given":"Partha","family":"Pande","sequence":"additional","affiliation":[{"name":"EECS, Washington State University","place":["Pullman, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5045-5535","authenticated-orcid":false,"given":"Umit","family":"Ogras","sequence":"additional","affiliation":[{"name":"University of Wisconsin-Madison","place":["Madison, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2025,9,26]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"2021. 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