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- 10943420211027539 type Paper assertion.
- 10943420211027539 type Resource assertion.
- 10943420211027539 type MediaObject assertion.
- 10943420211027539 description "Abstract Clouds represent a key uncertainty in future climate projection. 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." assertion.
- 10943420211027539 dateCreated "2022-03-22 10:25:06.625346+00:00" assertion.
- 10943420211027539 name "Unprecedented cloud resolution in a GPU-enabled full-physics atmospheric climate simulation on OLCF’s summit supercomputer" assertion.
- 10943420211027539 contentUrl "https://journals-sagepub-com.ezproxy.uio.no/doi/full/10.1177/10943420211027539" assertion.
- 10943420211027539 creator mailto:jean.iaquinta@geo.uio.no assertion.
- 10943420211027539 dateModified "2022-03-22 16:45:46.369940+00:00" assertion.
- 10943420211027539 license no-permission assertion.
- 10943420211027539 sdDatePublished "2022-03-22 10:25:06.625346+00:00" assertion.
- 10943420211027539 doi "10.1177/10943420211027539" assertion.
- 10943420211027539 author mailto:jean.iaquinta@geo.uio.no assertion.