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- W4289828023 abstract "The present work investigates the modeling of pre-exascale input/output (I/O) workloads of Adaptive Mesh Refinement (AMR) simulations through a simple proxy application. We collect data from the AMReX Castro framework running on the Summit supercomputer for a wide range of scales and mesh partitions for the hydrodynamic Sedov case as a baseline to provide sufficient coverage to the formulated proxy model. The non-linear analysis data production rates are quantified as a function of a set of input parameters such as output frequency, grid size, number of levels, and the Courant-Friedrichs-Lewy (CFL) condition number for each rank, mesh level and simulation time step. Linear regression is then applied to formulate a simple analytical model which allows to translate AMReX inputs into MACSio proxy I/O application parameters, resulting in a simple kernel approximation for data production at each time step. Results show that MACSio can simulate actual AMReX non-linear static I/O workloads to a certain degree of confidence on the Summit supercomputer using the present methodology. The goal is to provide an initial level of understanding of AMR I/O workloads via lightweight proxy applications models to facilitate autotune data management strategies in anticipation of exascale systems." @default.
- W4289828023 created "2022-08-05" @default.
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- W4289828023 date "2022-05-01" @default.
- W4289828023 modified "2023-10-16" @default.
- W4289828023 title "Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications" @default.
- W4289828023 doi "https://doi.org/10.1109/ipdpsw55747.2022.00153" @default.
- W4289828023 hasPublicationYear "2022" @default.
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