Simulating Fluid Flows on the Tensor Processing Unit Platform

ORAL

Abstract

A simulation framework is developed for predicting complex flows on Tensor Processing Unit (TPU) platforms. The simulation framework solves the three-dimensional Navier-Stokes equations along with constitutive models for fluid dynamics, combustion, heat-transfer, and other thermodynamic processes. One of the applications of this simulation framework is to study wildfire propagations. This framework is validated by considering predictions of prescribed wildfires with a wide range of physical factors including wind speed, terrains, fuel density, and moisture. Additionally, we simulated the full event of the 2017 Tubbs fire. These high-fidelity simulations generated by the TPU simulation framework runs significantly faster than conventional CPU-based CFD softwares, also at a lower computational cost, which provides a foundation for studying the physical insights of wildfire propagations scientifically.

Presenters

  • Qing Wang

    • Stanford University

Authors

  • Qing Wang

    • Stanford University
  • Xinle Liu

    • Google
  • Sheide Chammas

    • Google
  • Vivian Yang

    • Google Inc
  • Matthias Ihme

    • Stanford Univ
    • Stanford University
  • Yi-Fan Chen

    • Google