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Efficient algorithms for large-scale quantum transport calculations.

Sascha Brück1, Mauro Calderara1, Mohammad Hossein Bani-Hashemian1

  • 1Integrated Systems Laboratory, ETH Zürich, 8092 Zürich, Switzerland.

The Journal of Chemical Physics
|August 24, 2017
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Summary
This summary is machine-generated.

New massively parallel algorithms accelerate quantum transport simulations. These methods leverage hybrid computing architectures, significantly reducing computational time for first-principles calculations.

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Area of Science:

  • Computational physics
  • Quantum mechanics
  • Materials science

Background:

  • Quantum transport simulations are computationally intensive.
  • Accurate simulations require solving the Schrödinger equation and determining boundary conditions.

Purpose of the Study:

  • To develop massively parallel algorithms for first-principles quantum transport simulations.
  • To reduce the computational burden and time required for these simulations.

Main Methods:

  • Utilizing hybrid computer architectures (CPUs and GPUs).
  • Employing contour integration for eigenvalue problems (open boundary conditions).
  • Using the SplitSolve algorithm on GPUs for solving the Schrödinger equation.

Main Results:

  • Achieved a reduction in computational time by up to two orders of magnitude.
  • Successfully implemented parallel algorithms on modern hardware.

Conclusions:

  • The developed algorithms offer a significant speedup for quantum transport simulations.
  • Hybrid computing architectures are effective for accelerating first-principles calculations.