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The overall strategy couples a finite-difference time-domain approach for Maxwell\u2019s equations to a magnetization model described by the Landau\u2013Lifshitz\u2013Gilbert equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, which is primarily being developed for plasma wakefield accelerator modeling. Our temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal temporal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59\u00d7) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter. <\/jats:p>","DOI":"10.1177\/10943420211057906","type":"journal-article","created":{"date-parts":[[2022,1,15]],"date-time":"2022-01-15T13:04:52Z","timestamp":1642251892000},"page":"167-181","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["A massively parallel time-domain coupled electrodynamics\u2013micromagnetics solver"],"prefix":"10.1177","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5863-8275","authenticated-orcid":false,"given":"Zhi","family":"Yao","sequence":"first","affiliation":[{"name":"Lawrence Berkeley National Laboratory, Berkeley, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9432-2091","authenticated-orcid":false,"given":"Revathi","family":"Jambunathan","sequence":"additional","affiliation":[{"name":"Lawrence Berkeley National 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