# Parallel Transport Time-Dependent Density Functional Theory Calculations with Hybrid Functional on Summit

## TL;DR

This paper presents a GPU-accelerated parallel transport gauge method for hybrid functional real-time TDDFT, enabling large-scale simulations of over 1000 atoms efficiently on Summit supercomputer.

## Contribution

It introduces a novel parallel transport gauge formalism and GPU implementation that significantly accelerates hybrid functional rt-TDDFT calculations for large systems.

## Key findings

- Achieved efficient scaling to 786 GPUs for 1536 silicon atoms
- Reduced simulation time to 1.5 hours per femtosecond
- Enabled large system rt-TDDFT simulations with over 1000 atoms

## Abstract

Real-time time-dependent density functional theory (rt-TDDFT) with hybrid exchange-correlation functional has wide-ranging applications in chemistry and material science simulations. However, it can be thousands of times more expensive than a conventional ground state DFT simulation, hence is limited to small systems. In this paper, we accelerate hybrid functional rt-TDDFT calculations using the parallel transport gauge formalism, and the GPU implementation on Summit. Our implementation can efficiently scale to 786 GPUs for a large system with 1536 silicon atoms, and the wall clock time is only 1.5 hours per femtosecond. This unprecedented speed enables the simulation of large systems with more than 1000 atoms using rt-TDDFT and hybrid functional.