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Modeling pre-Exascale AMR Parallel I/O Workloads via Proxy Applications...

by William F Godoy, Jenna Delozier, Gregory R Watson
Publication Type
Conference Paper
Book Title
IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)
Publication Date
Page Numbers
952 to 961
Publisher Location
United States of America
Conference Name
36th IEEE International Parallel and Distributed Processing Symposium (IPDPS): iWAPT The Seventeenth International Workshop on Automatic Performance Tuning
Conference Location
Lyon (moved to virtual), France
Conference Sponsor
Conference Date

The present work investigates the modeling of preexascale 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 nonlinear “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.