论文标题
部分可观测时空混沌系统的无模型预测
Accelerating Physics Simulations with TPUs: An Inundation Modeling Example
论文作者
论文摘要
硬件加速器（例如张量处理单元（TPU））在相对于中央处理单元（CPU）等硬件加速器（TPU）的最新进展不仅用于机器学习，而且在此处证明，也用于科学建模和计算机模拟。为了研究用于分布式科学计算的TPU硬件，我们求解部分微分方程（PDE），用于对流体进行物理模拟以建模河流洪水。我们证明了TPU在CPU上实现了两个数量级的速度。在TPU上运行物理模拟可以通过Google Cloud平台公开访问，我们发布了模拟的Python Interactive Notebook版本。
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.
