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. 2021 Dec 14;17(12):7447-7467.
doi: 10.1021/acs.jctc.1c00562. Epub 2021 Nov 2.

Inq, a Modern GPU-Accelerated Computational Framework for (Time-Dependent) Density Functional Theory

Xavier Andrade  1 , Chaitanya Das Pemmaraju  2 , Alexey Kartsev  2 , Jun Xiao  2 , Aaron Lindenberg  2 , Sangeeta Rajpurohit  3 , Liang Z Tan  3 , Tadashi Ogitsu  1 , Alfredo A Correa  1
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Free article

Inq, a Modern GPU-Accelerated Computational Framework for (Time-Dependent) Density Functional Theory

Xavier Andrade et al. J Chem Theory Comput. .
Free article

Abstract

We present inq, a new implementation of density functional theory (DFT) and time-dependent DFT (TDDFT) written from scratch to work on graphic 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.

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