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'Diet GMTKN55' offers accelerated benchmarking through a representative subset approach.

Tim Gould1

  • 1Qld Micro- and Nanotechnology Centre, Griffith University, Nathan, Qld 4111, Australia. t.gould@griffith.edu.au.

Physical Chemistry Chemical Physics : PCCP
|November 3, 2018
PubMed
Summary

The GMTKN55 protocol benchmarks density functional approximations but is computationally expensive. New smaller subsets (30, 100, 150 systems) accurately reproduce full database results, offering a cost-effective alternative for computational chemistry analysis.

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Area of Science:

  • Computational Chemistry
  • Quantum Chemistry
  • Materials Science

Background:

  • The GMTKN55 protocol provides comprehensive benchmarking for density functional approximations.
  • Its extensive nature (1500 values, ~2500 systems) leads to high computational costs.

Purpose of the Study:

  • To introduce smaller, computationally efficient subsets of the GMTKN55 database.
  • To validate these subsets for reproducing key benchmarking results and rankings.
  • To offer a cost-effective alternative for evaluating density functional approximations.

Main Methods:

  • Development of three reduced GMTKN55 subsets (30, 100, 150 systems).
  • Utilizing a stochastic genetic algorithm for subset selection.
  • Comparison of results from subsets against the full GMTKN55 database.

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Main Results:

  • The developed subsets accurately reproduce key findings and rankings from the full GMTKN55 protocol.
  • The smaller subsets offer a significant reduction in computational cost.
  • Results for the MGCDB84 database are also presented.

Conclusions:

  • Reduced GMTKN55 subsets provide a viable and efficient alternative for benchmarking density functional approximations.
  • These subsets maintain the integrity of the original protocol's findings.
  • The approach facilitates broader application of rigorous DFT benchmarking.