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Accelerating Chemistry Modules in Atmospheric Models Using GPUs
Christian Guzman-Ruiz, Barcelona Supercomputing Center
We'll explore a novel solution to speed up chemistry modules in atmospheric models. The Multiscale Online Nonhydrostatic AtmospheRe CHemistry model (MONARCH), a chemical weather prediction system developed by the Barcelona Supercomputing Center, is used as our test bed. The model implements a new flexible treatment for gas- and aerosol-phase chemical processes, Chemistry Across Multiple Phases (CAMP), that allows multiple chemical processes (such as gas- and aerosol-phase chemical reactions, emissions, deposition, photolysis, and mass-transfer) to be solved simultaneously as a single system. We'll discuss innovative ways to speed up the CAMP module, including reducing memory accesses, multiple-cell chemistry solving, adaptation of the most time-consuming functions to GPUs, and heterogeneous computation approaches for CPU/GPU execution. We'll compare the optimized model to state-of-the art chemistry solvers commonly used in the earth sciences community (for example, EBI and KPP).