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While explicit cloud resolution remains beyond our computational grasp for global climate, we can incorporate important cloud effects through a computational middle ground called the Multi-scale Modeling Framework (MMF), also known as Super Parameterization. This algorithmic approach embeds high-resolution Cloud Resolving Models (CRMs) to represent moist convective processes within each grid column in a Global Climate Model (GCM). The MMF code requires no parallel data transfers and provides a self-contained target for acceleration. This study investigates the performance of the Energy Exascale Earth System Model-MMF (E3SM-MMF) code on the OLCF Summit supercomputer at an unprecedented scale of simulation. Hundreds of kernels in the roughly 10K lines of code in the E3SM-MMF CRM were ported to GPUs with OpenACC directives. A high-resolution benchmark using 4600 nodes on Summit demonstrates the computational capability of the GPU-enabled E3SM-MMF code in a full physics climate simulation. <\/jats:p>","DOI":"10.1177\/10943420211027539","type":"journal-article","created":{"date-parts":[[2021,7,16]],"date-time":"2021-07-16T13:49:45Z","timestamp":1626443385000},"page":"93-105","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":24,"title":["Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF\u2019s summit supercomputer"],"prefix":"10.1177","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4764-3348","authenticated-orcid":false,"given":"Matthew R","family":"Norman","sequence":"first","affiliation":[{"name":"National Center for Computational Sciences,Oak Ridge National Laboratory, Oak Ridge, TN, USA"}]},{"given":"David 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