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

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.

• Publication year

  2021

• Venue

  Journal of Chemical Theory and Computation

• Publication date

  2021-06-07

• Fields of study

  Chemistry, Medicine, Physics, Computer Science

• Identifiers
  DOI 10.1021/acs.jctc.1c00562arXiv 2106.03872PMID 34726888
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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