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Linear scaling fundamentals and algorithms

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G. Scuseria (GAUSSIAN), M. Head-Gordon (Q-CHEM) - Numerical ... S. Kenny &. A Horsfield (PLATO) - Gaussian with hybrid machinery. J. Hutter, M. Parrinello ... – PowerPoint PPT presentation

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Title: Linear scaling fundamentals and algorithms


1
Linear scaling fundamentals and algorithms
José M. Soler Universidad Autónoma de Madrid
2
Linear scaling Order(N)
CPU load
3
N
N
Early 90s
N ( atoms)
100
3
Order-N DFT
  • Find density and hamiltonian (80 of code)
  • Find eigenvectors and energy (20 of code)
  • Iterate SCF loop
  • Steps 1 and 3 spared in tight-binding schemes

4
DFT successful but heavy
  • Computationally much more expensive than
    empirical atomic simulations
  • Several hundred atoms in massively parallel
    supercomputers

5
Key to O(N) locality
Large system
Divide and conquer W. Yang, Phys. Rev. Lett.
66, 1438 (1992) Nearsightedness W. Kohn,
Phys. Rev. Lett. 76, 3168 (1996)
6
Basis sets for linear-scaling DFT
  • LCAO - Gaussian based QC machinery
  • G. Scuseria
    (GAUSSIAN),
  • M. Head-Gordon
    (Q-CHEM)
  • - Numerical atomic orbitals
    (NAO)
  • SIESTA
  • S. Kenny . A
    Horsfield (PLATO)
  • - Gaussian with hybrid
    machinery
  • J. Hutter, M.
    Parrinello
  • Bessel functions in ovelapping spheres
  • P. Haynes M. Payne
  • B-splines in 3D grid
  • D. Bowler M.
    Gillan
  • Finite-differences (nearly O(N)) J. Bernholc

7
Divide and conquer
Weitao Yang (1992)
8
Fermi operator/projector
Goedecker Colombo (1994)
9
Density matrix functional
Li, Nunes Vanderbilt (1993)
10
Wannier O(N) functional
  • Mauri, Galli Car, PRB 47, 9973 (1993)
  • Ordejon et al, PRB 48, 14646 (1993)

11
Order-N vs KS functionals
12
Chemical potential
Kim, Mauri Galli, PRB 52, 1640 (1995)
  • ?(r) 2?ij ?i(r) (2?ij-Sij) ?j(r)
  • EO(N) Tr (2I-S) H states
    electron pairs
  • ? Local minima
  • EKMG Tr (2I-S) (H-?S) states gt
    electron pairs
  • ? chemical potential (Fermi energy)
  • Ei lt ? ? ?i ? 0
  • Ei gt ? ? ?i ? 1
  • Difficulties
    Solutions
  • Stability of N(?) Initial
    diagonalization
  • First minimization of EKMG Reuse previous
    solutions

13
Orbital localization
??
?i(r) ?? ci? ??(r)
14
Convergence with localisation radius
Si supercell, 512 atoms
Relative Error ()
Rc (Ang)
15
Sparse vectors and matrices
Restore to zero xi ? 0 only
16
Actual linear scaling
c-Si supercells, single-?
Single Pentium III 800 MHz. 1 Gb RAM
132.000 atoms in 64 nodes
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