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Accelerating physics simulations with tensor processing units: An inundation modeling example

R. Lily Hu, Damien M. Pierce, Yusef Shafi, Anudhyan Boral, Владимир Анисимов, Sella Nevo, Yifan Chen

2022The International Journal of High Performance Computing Applications15 citationsDOI

Abstract

Recent advancements in hardware accelerators such as Tensor Processing Units (TPUs) speed up computation time relative to Central Processing Units (CPUs) not only for machine learning but, as demonstrated here, also for scientific modeling and computer simulations. To study TPU hardware for distributed scientific computing, we solve partial differential equations (PDEs) for the physics simulation of fluids to model riverine floods. We demonstrate that TPUs achieve a two orders of magnitude speedup over CPUs. Running physics simulations on TPUs is publicly accessible via the Google Cloud Platform, and we release a Python interactive notebook version of the simulation.

Topics & Concepts

Python (programming language)SpeedupComputational scienceComputer scienceComputationTensor (intrinsic definition)Parallel computingCloud computingAlgorithmOperating systemGeometryMathematicsComputational Physics and Python ApplicationsFlood Risk Assessment and ManagementTropical and Extratropical Cyclones Research
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