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A unified object\u2010oriented central processing unit (CPU)\u00a0+\u00a0graphics processing unit (GPU) approach is complemented with an inter\u2010device communication layer, enabling both coarse and fine\u2010grain parallelism on hyperbolic solvers. The approach involves the combination of three different programming platforms, namely OpenMP, CUDA and MPI. The efficiency of this distributed\u2010heterogeneous approach is quantified under static and dynamic loads on consumer and professional grade CPUs and GPUs. An asynchronous communications scheme is implemented and described, showing very reduced overheads and a nearly linear scalability for multiple device combinations. For simulations (or systems) with non\u2010homogeneous workloads (or devices) the domain decomposition algorithm incorporates a low\u2010frequency load\u2010to\u2010device fitting function to ensure computational balance. A real\u2010world application to high\u2010resolution hydrodynamic modelling is presented: the propagation of a tsunami in the estuary a large river and its run\u2010up in an urban mesh. The proposed implementation shows speedups of up to two orders of magnitude, opening new perspectives for solvers with high\u2010demand requirements but relatively simple hardware in multi\u2010architecture machines.<\/jats:p>","DOI":"10.1029\/2024ms004602","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T08:44:34Z","timestamp":1764146674000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Distributed\u2010Heterogeneous Design for Explicit Hyperbolic Solvers. Application to Tsunami Urban Run\u2010Up Modelling"],"prefix":"10.1029","volume":"17","author":[{"given":"Daniel A. 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