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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1.080 Topics available

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977 Locations available

693.932 PEOPLE
693.932 People People

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (7/7 displayed)

  • 2015Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models101citations
  • 2015Quantum Chemistry for Solvated Molecules on Graphical Processing Units Using Polarizable Continuum Models.citations
  • 2015An atomic orbital-based formulation of analytical gradients and nonadiabatic coupling vector elements for the state-averaged complete active space self-consistent field method on graphical processing units68citations
  • 2013Generating Efficient Quantum Chemistry Codes for Novel Architectures360citations
  • 2013Generating Efficient Quantum Chemistry Codes for Novel Architectures.citations
  • 2011Dynamic Precision for Electron Repulsion Integral Evaluation on Graphical Processing Units (GPUs)150citations
  • 2011Dynamic Precision for Electron Repulsion Integral Evaluation on Graphical Processing Units (GPUs).citations

Places of action

Chart of shared publication
Liu, Fang
2 / 20 shared
Kulik, Heather J.
2 / 3 shared
Martinez, Todd J.
4 / 8 shared
Martínez, Todd J.
2 / 3 shared
Hohenstein, Edward G.
1 / 1 shared
Snyder, James W.
1 / 1 shared
Titov, Alexey V.
2 / 2 shared
Ufimtsev, Ivan S.
4 / 8 shared
Chart of publication period
2015
2013
2011

Co-Authors (by relevance)

  • Liu, Fang
  • Kulik, Heather J.
  • Martinez, Todd J.
  • Martínez, Todd J.
  • Hohenstein, Edward G.
  • Snyder, James W.
  • Titov, Alexey V.
  • Ufimtsev, Ivan S.
OrganizationsLocationPeople

article

Generating Efficient Quantum Chemistry Codes for Novel Architectures

  • Luehr, Nathan
  • Titov, Alexey V.
  • Ufimtsev, Ivan S.
  • Martinez, Todd J.
Abstract

We describe an extension of our graphics processing unit (GPU) electronic structure program TeraChem to include atom-centered Gaussian basis sets with d angular momentum functions. This was made possible by a "meta-programming" strategy that leverages computer algebra systems for the derivation of equations and their transformation to correct code. We generate a multitude of code fragments that are formally mathematically equivalent, but differ in their memory and floating-point operation footprints. We then select between different code fragments using empirical testing to find the highest performing code variant. This leads to an optimal balance of floating-point operations and memory bandwidth for a given target architecture without laborious manual tuning. We show that this approach is capable of similar performance compared to our hand-tuned GPU kernels for basis sets with s and p angular momenta. We also demonstrate that mixed precision schemes (using both single and double precision) remain stable and accurate for molecules with d functions. We provide benchmarks of the execution time of entire self-consistent field (SCF) calculations using our GPU code and compare to mature CPU based codes, showing the benefits of the GPU architecture for electronic structure theory with appropriately redesigned algorithms. We suggest that the meta-programming and empirical performance optimization approach may be important in future computational chemistry applications, especially in the face of quickly evolving computer architectures.

Topics
  • impedance spectroscopy
  • theory