Alhaddad, SamerSamerAlhaddadFörstner, JensJensFörstnerGroth, StefanStefanGrothGrünewald, DanielDanielGrünewaldGrynko, YevgenYevgenGrynkoHannig, FrankFrankHannigKenter, TobiasTobiasKenterPfreundt, Franz-JosefFranz-JosefPfreundtPlessl, ChristianChristianPlesslSchotte, MerlindMerlindSchotteSteinke, ThomasThomasSteinkeTeich, JürgenJürgenTeichWeiser, MartinMartinWeiserWende, FlorianFlorianWende2022-03-062022-03-062022https://publica.fraunhofer.de/handle/publica/27056010.1002/cpe.6616Solving partial differential equations (PDEs) on unstructured grids is a cornerstone of engineering and scientific computing. Heterogeneous parallel platforms, including CPUs, GPUs, and FPGAs, enable energy-efficient and computationally demanding simulations. In this article, we introduce the HighPerMeshes C++-embedded domain-specific language (DSL) that bridges the abstraction gap between the mathematical formulation of mesh-based algorithms for PDE problems on the one hand and an increasing number of heterogeneous platforms with their different programming models on the other hand. Thus, the HighPerMeshes DSL aims at higher productivity in the code development process for multiple target platforms. We introduce the concepts as well as the basic structure of the HighPerMeshes DSL, and demonstrate its usage with three examples. The mapping of the abstract algorithmic description onto parallel hardware, including distributed memory compute clusters, is presented. A code generator and a matching back end allow the acceleration of HighPerMeshes code with GPUs. Finally, the achievable performance and scalability are demonstrated for different example problems.encode generationdistributed computingdomain-specific languagenumerical algorithm003005006519journal article