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Dynamic task fusion for a block-structured finite volume solver over a dynamically adaptive mesh with local time stepping

Li, Baojiu and Schulz, Holger and Weinzierl, Tobias and Han, Zhang (2022) 'Dynamic task fusion for a block-structured finite volume solver over a dynamically adaptive mesh with local time stepping.', in High Performance Computing 37th International Conference, ISC High Performance 2022, Hamburg, Germany, May 29 – June 2, 2022, Proceedings. , pp. 153-173. Lecture Notes in Computer Science., 13289


Load balancing of generic wave equation solvers over dynamically adaptive meshes with local time stepping is dicult, as the load changes with every time step. Task-based programming promises to mitigate the load balancing problem. We study a Finite Volume code over dynamically adaptive block-structured meshes for two astrophysics simulations, where the patches (blocks) dene tasks. They are classied into urgent and low priority tasks. Urgent tasks are algorithmically latencysensitive. They are processed directly as part of our bulk-synchronous mesh traversals. Non-urgent tasks are held back in an additional task queue on top of the task runtime system. If they lack global side-eects, i.e. do not alter the global solver state, we can generate optimised compute kernels for these tasks. Furthermore, we propose to use the additional queue to merge tasks without side-eects into task assemblies, and to balance out imbalanced bulk synchronous processing phases.

Item Type:Book chapter
Full text:(AM) Accepted Manuscript
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Publisher statement:The final authenticated version is available online at
Date accepted:29 March 2022
Date deposited:18 August 2022
Date of first online publication:29 May 2022
Date first made open access:14 September 2022

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