Large scale quantum chemistry with Tensor Processing Units
arXiv:2202.01255 · doi:10.1021/acs.jctc.2c00876
Abstract
We demonstrate the use of Google's 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 towards accessible and systematic use of conventional DFT, free of any system-specific constraints, at unprecedented scales.
References in corpus (7)
- NWChem: Past, Present, and Future
- Quantum embedding theories
- DFT-FE 1.0: A massively parallel hybrid CPU-GPU density functional theory code using finite-element discretization
- A TensorFlow Simulation Framework for Scientific Computing of Fluid Flows on Tensor Processing Units
- Simulation of quantum many-body dynamics with Tensor Processing Units: Floquet prethermalization
- Large Scale Distributed Linear Algebra With Tensor Processing Units
- Trends in atomistic simulation software usage
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