Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (3/3 displayed)

  • 2015Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models.citations
  • 2011Dynamic Precision for Electron Repulsion Integral Evaluation on Graphical Processing Units (GPUs).citations
  • 2008Quantum Chemistry on Graphical Processing Units. 1. Strategies for Two-Electron Integral Evaluation.citations

Places of action

Chart of shared publication
Luehr, Nathan
2 / 7 shared
Liu, Fang
1 / 20 shared
Kulik, Heather J.
1 / 3 shared
Ufimtsev, Ivan S.
2 / 8 shared
Chart of publication period
2015
2011
2008

Co-Authors (by relevance)

  • Luehr, Nathan
  • Liu, Fang
  • Kulik, Heather J.
  • Ufimtsev, Ivan S.
OrganizationsLocationPeople

article

Quantum Chemistry on Graphical Processing Units. 1. Strategies for Two-Electron Integral Evaluation.

  • Ufimtsev, Ivan S.
  • Martínez, Todd J.
Abstract

Modern videogames place increasing demands on the computational and graphical hardware, leading to novel architectures that have great potential in the context of high performance computing and molecular simulation. We demonstrate that Graphical Processing Units (GPUs) can be used very efficiently to calculate two-electron repulsion integrals over Gaussian basis functions [Formula: see text] the first step in most quantum chemistry calculations. A benchmark test performed for the evaluation of approximately 10(6) (ss|ss) integrals over contracted s-orbitals showed that a naïve algorithm implemented on the GPU achieves up to 130-fold speedup over a traditional CPU implementation on an AMD Opteron. Subsequent calculations of the Coulomb operator for a 256-atom DNA strand show that the GPU advantage is maintained for basis sets including higher angular momentum functions.

Topics
  • impedance spectroscopy
  • simulation