使用张量处理单元的大规模量子化学
Large Scale Quantum Chemistry with Tensor Processing Units.
作者信息
Pederson Ryan, Kozlowski John, Song Ruyi, Beall Jackson, Ganahl Martin, Hauru Markus, Lewis Adam G M, Yao Yi, Mallick Shrestha Basu, Blum Volker, Vidal Guifre
机构信息
Department of Physics and Astronomy, University of California, Irvine, California92617, United States.
X, the Moonshot Factory, Mountain View, California94043, United States.
出版信息
J Chem Theory Comput. 2023 Jan 10;19(1):25-32. doi: 10.1021/acs.jctc.2c00876. Epub 2022 Dec 12.
We demonstrate the use of Googles cloud-based Tensor Processing Units (TPUs) to accelerate and scale up conventional (cubic-scaling) density functional theory (DFT) calculations. Utilizing 512 TPU cores, we accomplish the largest such DFT computation to date, with 247848 orbitals, corresponding to a cluster of 10327 water molecules with 103270 electrons, all treated explicitly. Our work thus paves the way toward accessible and systematic use of conventional DFT, free of any system-specific constraints, at unprecedented scales.
我们展示了如何使用谷歌基于云的张量处理单元（TPU）来加速和扩大传统（立方标度）密度泛函理论（DFT）计算。利用512个TPU核心，我们完成了迄今为止此类最大规模的DFT计算，涉及247848个轨道，对应于一个由10327个水分子和103270个电子组成的簇，所有这些都进行了显式处理。因此，我们的工作为以前所未有的规模无障碍、系统地使用传统DFT铺平了道路，且不受任何特定系统的限制。
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