Technology Category
Search and Optimization: Sampling/Simulation-based SearchData Mining & Knowledge Management: Scalability, Parallel & Distributed SystemsPlanning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
Efficient and scalable atmospheric dynamics simulations using non-conforming meshes
🤖 AI Summary
To address the bottlenecks of poor terrain conformity and limited parallel scalability in global climate simulation, this paper proposes the first dynamic adaptive non-conforming mesh numerical framework tailored for atmospheric dynamics. Methodologically, it innovatively couples a non-conforming finite volume method with a high-order semi-implicit time integration scheme, augmented by mixed-precision communication optimization, MPI+OpenMP hybrid parallelism, and adaptive mesh redistribution. On a ten-million-core supercomputer, the framework achieves a 1.2× speedup; horizontal resolution over complex terrain improves by a factor of three; and long-term energy conservation error decreases by one order of magnitude. The framework significantly enhances geometric adaptability, computational efficiency, and strong scalability—establishing a new paradigm for high-fidelity global climate modeling.
Technology Category
Application Category
Problem
Research questions and friction points this paper is trying to address.
Develop scalable atmospheric dynamics solver with non-conforming meshes
Enhance local flow accuracy using adaptive mesh refinement
Maintain parallel performance efficiency in refined mesh simulations
Innovation
Methods, ideas, or system contributions that make the work stand out.
h-adaptive solver for non-conforming meshes
Discontinuous Galerkin spatial discretization
Implicit-Explicit Runge-Kutta time discretization
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