Dynamic Adaptive Refinement In Earth System Modelling

: Increasing the mesh resolution is one the most important tools for increasing the accuracy of numerical simulations. However, increasing the mesh resolution globally increases the amount of data and computational time substantially. In the exascale-era sub-km meshes are becoming more and more popular for atmospheric models, making it especially difficult to manage the vast amount of data efficiently. With dynamic adaptive mesh refinement (AMR) we locally control the resolution of a mesh in areas of interest, using a fine resolution only where it is explicitely needed and keeping the mesh coarse elsewhere. Thus, we concentrate the data and computing power and significantly reduce the simulation costs while keeping the same numerical accuracy. Vice versa, the resolution can be increased while keeping the same runtime. Managing adaptive meshes induces new challenges such as load-balancing, mesh management, ghost layer computation etc. Developments in the recent years have extended the scalable and efficicient tree-based AMR approach from quadrilaterals/hexahedra to various element shapes such as triangles, tetrahedra, pyramids or prisms and have been implemented in our AMR library t8code. It is a third-party library that adresses these challenges and can be integrated by solver environments in order to enable AMR. In our presentation we will give an introduction to AMR and how we use it for atmospheric simulations. We will give an overview of ongoing and past projects, such as our contributions to PilotLab Exascale Earth Sytem Modelling (Pl-ExaESM) or the lossy data compression for data coming from atmospheric simulations. Furthermore, we will demonstrate the efficiency of our methods with recent benchmark results on current supercomputers, showing that t8code scales on up to at least 1 million MPI ranks and over 1 Trillion mesh elements

t8code - scalable and modular adaptive mesh refinement

t8code is a versatile open source library for parallel adaptive mesh refinement on hybrid meshes. [1] It is exascale-ready and capable of efficiently managing meshes with up to a trillion elements distributed on a million of cores as already shown in a peer-reviewed research paper. [2] On the top-level, t8code uses forests of trees to represent unstructured meshes with complex geometries. Space-filling curves index individual elements within a forest, which requires only minimal amounts of memory allowing for efficient and scalable algorithms of mesh management. In contrast to existing solutions, t8code has the capability to manage an arbitrary number of tetrahedra, hexahedra, prisms and pyramids within the same mesh. With this poster we want to present the first official release (v1.0) of our software and give a quick overview over its main features. Besides presenting the core algorithms of t8code, we give application scenarios on how our library integrates into major simulation frameworks for weather forecasting, climate modeling and engineering; and how they benefit from our approach to do AMR. [1] https://github.com/DLR-AMR/t8code [2] https://epubs.siam.org/doi/abs/10.1137/20M138303

t8code

t8code is a C/C++ library to manage parallel adaptive meshes with various element types. t8code uses a collection (a forest) of multiple connected adaptive space-trees in parallel and scales to at least one million MPI ranks and over 1 Trillion mesh elements. t8code uses space-filling curves (SFCs) to manage the adaptive refinement and efficiently store the mesh elements and associated data

The Power of Modular Tree-Based AMR - Resolving Hanging Nodes and Cutting Holes

We discuss recent developments in scalable adaptive mesh refinement (AMR). The t8code library offers fast and efficient tree-based (space-filling curve) adaptive mesh refinement solutions for application codes that require meshes. t8code extends the space-filling curve (SFC) techniques from quadrilaterals and hexahedra to all element shapes via an abstract interface. In particular we offer implementations for vertices, lines, quads, triangles, tetrahedra, hexahedra, prisms and pyramids, and also support meshes including different element shapes. The abstract interface allows us to further extend the SFC techniques to non-standard use cases that enable fast and scalable AMR for a variety of use cases. In particular we present the feature deleting elements from the mesh and the feature subelements. Subelements itself are very powerful in that they allow for a variety of new AMR option. One application of us is to remove hanging nodes from quad based AMR. Other applications include the definition of boundary layer (for example around airfoils), anisotropic refinement or subgrids for GPU computations

t8code v. 1.0 - Modular Adaptive Mesh Refinement in the Exascale Era

In this note we present version 1.0 of our software library t8code for scalable dynamic adaptive mesh refinement (AMR) officially released in 2022. t8code is written in C/C++, open source, and readily available at www.dlr-amr.github.io/t8code. The library provides fast and memory efficient parallel algorithms for dynamic AMR to handle tasks such as mesh adaptation, load-balancing, ghost computation, feature search and more. t8code can manage meshes with over one trillion mesh elements and scales up to one million parallel processes. It is intended to be used as mesh management back end in scientific and engineering simulation codes paving the way towards high-performance applications of the upcoming exascale era