We present INQ, a new implementation of density functional theory (DFT) and time-dependent DFT (TDDFT) written from scratch to work on graphical processing units (GPUs). Besides GPU support, INQ makes use of modern code design features and takes advantage of newly available hardware. By designing the code around algorithms, rather than against specific implementations and numerical libraries, we aim to provide a concise and modular code. The result is a fairly complete DFT/TDDFT implementation in roughly 12,000 lines of open-source C++ code representing a modular platform for community-driven application development on emerging high-performance computing architectures for the simulation of materials.
@article{arxiv.2106.03872,
title = {INQ, a modern GPU-accelerated computational framework for (time-dependent) density functional theory},
author = {Xavier Andrade and Chaitanya Das Pemmaraju and Alexey Kartsev and Jun Xiao and Aaron Lindenberg and Sangeeta Rajpurohit and Liang Z. Tan and Tadashi Ogitsu and Alfredo A. Correa},
journal= {arXiv preprint arXiv:2106.03872},
year = {2021}
}