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Parallel Computing—a route to complexity and reality in material simulations

Parallel Computing—a route to complexity and reality in material simulations. Shiwu Gao Department of Applied Physics Chalmers/Göteborg University. Parallel computing and materials simulations. Water-metal interface. Dynamics of electron excitation/transfer. Biomembrane

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Parallel Computing—a route to complexity and reality in material simulations

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  1. Parallel Computing—a route to complexity and reality in material simulations Shiwu Gao Department of Applied Physics Chalmers/Göteborg University

  2. Parallel computing and materials simulations Water-metal interface Dynamics of electron excitation/transfer Biomembrane Aquaporin water channel in membrane K. Murata et al, Nature, 407, 599 (2002)

  3. Macroscopic (meter, hour) Bottom-up approach Mesoscopic Kinetics Energetics Atomic Electronic (Å, fs) • Theoretical approach based on: • Fundamental laws of physics • Computer modeling and simulations

  4. Density Functional Theory based simulations Solving the Kohn-Sham Equations for all electorns Full-potential and pseudopotential methods -Ful-potential methods (FP-LAPW, FP-LMTO) accurate and slow -Pseudo-potential methods (VASP, CPMD, PWSCF) fast but with uncertainty in pseudopotentials

  5. Outline • Parallelization of WIEN package FP-(L)APW method • Applications - Hydrogen bonding by CH group - Pressure melting of confined water films

  6. + Accurate + Versatile -- Slow -- larger RAM WIEN97 (T. U. Vienna) Typical timing (s) Potential Eigenproblem Density Core Electron Mixing in/out data H/Cu(100) p(3x3) 3+2+5layers 29 atoms

  7. Timing in LAPW1 • Large memory needed for H,S RAM ~ M2 - Time-consuming H |Ψk>= εkS |Ψk> t ~ M3 For large systems (>30 atoms) - more than 90 % CPU time - severval GB RAM

  8. Parallelizing the eigenproblem (LAPW1) • Distributing and parallel • setting H and S 2. Parallelizing the eigensolver -Incorporating PQR -Writting an iterative parallel solver Myid = 0 1 2 3 0 1 2 3 0 PQR: X.B. Chi, Inst. Software, Chinese Academy of Sciences,Beijing

  9. Further Parallelizations + LAPW1 Distributing H S setting and parallelizing the eigensolver -Incorporating PQR -Writting an iterative parallel solver + LAPW2 and LAPW0 Distributing the calculation atom-wise + Implemeting the new APW+lo basis, E. Sjöstedt, Nordström, and Singh, Solid State Commun 114, 15 (2001) S. Gao, Comput. Phys. Commun. (to be published)

  10. Test example: C2H4+O2/Ag(110) coadsorption • 100 surface atoms • -Ag(110) 3x4x7=84 • -(C2H4+o2)x2=16 • 6 layer vacuum • 21x23x35 au3 • Dual basis • -Ag(110) LAPW • -molecules, APW+lo • 1-k point • 9 Ry cut-off structure • 13 -16 Ry in energy • 12 min/SCF 24 SGI3k • 12-15 Ionic steps/day

  11. Scaling on IBM SP3 (PDC, KTH) M=14400 Tested up to 48 CPUs + Nearly linear-scaling

  12. Scaling on Seth---Linux cluster at HPC2N Up to 128 CPUs Seth and SP3: 1) comparable scaling, 2) different in speed

  13. Summary on scaling and performance Applicable to large systems, as PW-PP methods

  14. Hydrogen bonding by CH group C2H4+O2/Ag(110)Expt: J. R. Hahn, W. Ho, UCITheory: S. W. Gao, Chalmers

  15. Why hydrogen bond with CH group • H-bond is ubiquetous in biomolecules and organics • Also of interest for fundamental studies • (Ionic, covelency, vdW?) • Usually with FH (VII), OH (VI), and NH(V) • due to the large affinity, favoring ionic coupling • H-bond with CH, weak—controversial • EHB < 1 kcal/mol (c.a. 43 meV)

  16. Building artificial complex with organics

  17. Questions: - Structure and orientations - Interaction between ethylene oxygen - IE-STS

  18. Distance-dependent interaction -27.4 meV -90.4 meV -6.6 meV In the gas phase: the interaction is negligible ~ + 10 meV

  19. Mechanism of H-bond formation--adsorption induced electron transfer

  20. Pressure Melting of Confined Water from ab initio Molecular Dynamics Simulation

  21. Background and Motivation • Special phenomena in confined water • Bio-membrane fusion: role of thin water films • Pressure: -phase control -material synthesis -mechanical stimuli in biology • Ice-skating and lubrication • How to characterize confined liquid water from computer simulations

  22. New water phases in confined water • Existence of solid-liquid critical points K.Koga et al.,Nature 412, 802 (2001)

  23. Bio-membrane Fusion Science 297, 1817 & 1878 (2002)

  24. Phase Diagram of Water Science 297, 1288 (2002)

  25. Simulation Method • VASP—Veinna ab intio simulation package (better adapted to MD simulations) • . • Slab representation in a supercell geometry: up to 48 Pt atoms and 32 H2O molecules

  26. Applying the pressure Pt ΔZ Water Pt

  27. Kinetic Energy vs. ΔZ Transition at volume change 6.6 % Bulk ice (expt.) 6.4 %

  28. Layer-resolved Ek~ΔZ 4th Layer 3rd Layer 2nd Layer 1st Layer

  29. Estimating the pressure P = F / S

  30. Trajectories of a molecule from the simulation ---- Before melting After melting ----

  31. Solid Ice vs. Liquid Water

  32. Hydrogen Bond Dynamics

  33. Pair Correlation Function

  34. Summary • Parallel WIEN for large-scale ab initio electron structure calculations • Applications in material simulations • Hydrogen bonding mechanism induced by adsorption • Pressure induced phase transitions of water films

  35. Parallel computing Route to complexity Single CPU processing

  36. Acknowledgements • Sheng Meng • Supported by VR • E. G. Wang’s (IOP, Beijing), B. Kasemo, Chalmers • P. Blaha (TU Vienna) • E. Sjöstedt, L. Nordström (Uppsala) • Technical support from (Ulf Andersson , Niclas Andersson, Torgny Faxen)

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