Technical Papers Archive

Large-Scale Materials Modeling at Quantum Accuracy: Ab Initio Simulations of Quasicrystals and Interacting Extended Defects in Metallic Alloys

Authors: Sambit Das, Bikash Kanungo, and Vishal Subramanian (University of Michigan); Gourab Panigrahi and Phani Motamarri (Indian Institute of Science); David Rogers (Oak Ridge National Laboratory (ORNL)); and Paul Zimmerman and Vikram Gavini (University of Michigan)

Abstract: Ab initio electronic-structure has remained dichotomous between achievable accuracy and length-scale. Quantum many-body (QMB) methods realize quantum accuracy but fail to scale. Density functional theory (DFT) scales favorably but remains far from quantum accuracy. We present a framework that breaks this dichotomy by use of three interconnected modules:

(i) invDFT: a methodological advance in inverse DFT linking QMB methods to DFT;

(ii) MLXC: a machine-learned density functional trained with invDFT data, commensurate with quantum accuracy;

(iii) DFT-FE-MLXC: an adaptive higher-order spectral finite-element (FE) based DFT implementation that integrates MLXC with efficient solver strategies and HPC innovations in FE-specific dense linear algebra, mixed-precision algorithms, and asynchronous compute-communication.

We demonstrate a paradigm shift in DFT that not only provides an accuracy commensurate with QMB methods in ground-state energies, but also attains an unprecedented performance of 659.7 PFLOPS (43.1% peak FP64 performance) on 619,124 electrons using 8,000 GPU nodes of Frontier supercomputer.




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