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Large Scale Quantum Chemistry with Tensor Processing Units

Ryan Pederson, John Kozlowski, Ruyi Song, Jackson Beall, Martin Ganahl, Markus Hauru, Adam G. M. Lewis, Yi Yao, Shrestha Basu Mallick, Volker Blüm, Guifré Vidal

2022Journal of Chemical Theory and Computation30 citationsDOI

Abstract

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.

Topics & Concepts

Atomic orbitalDensity functional theoryTensor (intrinsic definition)ScalingComputer scienceComputational scienceComputationCluster (spacecraft)Scale (ratio)Cloud computingElectronStatistical physicsComputational chemistryPhysicsChemistryQuantum mechanicsAlgorithmMathematicsGeometryOperating systemProgramming languagePure mathematicsAdvanced Chemical Physics StudiesMachine Learning in Materials ScienceSpectroscopy and Quantum Chemical Studies
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