学术报告 | Parallel Transport Time-Dependent Density Functional Theory

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. Recently we introduced the parallel transport gauge formulism, which can increase the rt-TDDFT time step by a factor of 100. Then we implemented the new algorithm on supercomputer 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.

主讲人简介

贾伟乐，2016年毕业于中科院大学，目前在加州大学伯克利分校做博士后。研究方向为并行计算，DFT计算方法，大规模异构计算算法。主要工作涉及平面波方法电子结构计算，异构线性标度算法，rt-TDDFT算法的研究，是平面波第一性原理计算软件PWmat的主要研发人员之一。