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					Capability Tasks in Ab Initio MD: the UK
       Car-Parrinello Consortium



                 Paul Madden
   Physical and Theoretical Chemistry Laboratory
                University of Oxford
               HPC Issues

• How to ensure resource is properly used
       expertise & back-up (code develop.)
       “tensioning” allocations
        fluctuations in personnel
 How to ensure benefit is shared by
  community (capability => exclusivity)
         e.g. by availability and maintenance
         of generally useable code
           UKCP (since ~1989)

• 13 Groups (in different universities)
• To use national HPC facilities for AIMD
• Funding from EPSRC (1 postdoc +
  12,000,000 processor hours over 3 years)
• Internal allocation of these resources
• Multi-code (CPMD, SIESTA,
                        vasp, CASTEP….),
  but collaborative development on CASTEP
                   CASTEP
•   (Adiabatic) AIMD – for Materials (ultrasoft-
    pseudopotentials, B-Z sampling,
    metals……)
•   Marketed by Accelrys (easy use, gui etc)
•   Accelrys – CLRC – UKCP agreement
    makes CASTEP free to UK academics
•   CLRC/EPSRC gives 1.5 FTEs for
    CASTEP/HPC development
•   UKCP gives new functionality to Accelrys
    (linear response phonons & polarizability; MLWFS – dipoles,
    quadrupoles, Born charges; finite displacement phonons;
    harmonic free energy…..)
                  HPCx
• 1024 IBM power 4 processors (+devel.)
• 6.6 TFlops + 1.28TB memory
• “Capability discounts” etc.– e.g. if
  T(512)/T(1024)>1.7 => 30% discount

• Processors organised in groups of 8
  (LPAR) v. good local comms.
• CASTEP scaled badly (fft => latency in All-
  to-All communication)
       Communication speedup

• All-to-All MPI          LPAR 1   LPAR 2
  communication
  between all processor   1    5   9    13
  pairs.                  2    6   10   14
• Instead, gather data    3    7   11   15
  within each LPAR
                          4    8   12   16
  (e.g. 1, 9, ..) and
  transfer 1  9 etc,
  then scatter within
  LPAR.
• M. Plummer (DL)
              Castep 2003 HPCx
               performance gain
                  Al2O3 120 atom cell, 5 k-points

           8000
           7000
           6000
Job time




           5000
           4000
           3000                                     Jan-03
           2000                                     Current 'Best'
           1000
              0
                   80     160     240     320

                   Total number of processors
              Castep 2003 HPCx
               performance gain
                   Al2O3 270 atom cell, 2 k-points


           20000

           15000
Job Time




           10000
                                                     Jan-03
            5000                                     Current 'Best'

               0
                    128        256       512

                    Total number of processors
                Phil Lindan – U. of Kent,
        Hydration of (110) surface of TiO2 (Rutile)



AIMD

 300K

81 H2O

72 ions

20 ps
            Linear Scaling Techniques
                              
 r , r          
                      
                        R r  K R r 
                          

                        R
   R       = lattice vectors

      
  K         = density kernel

    =
       
      R
            non-orthogonal generalised Wannier
               functions (NGWFs)
   P.D. Haynes, C.-K. Skylaris, O. Diéguez,
        A.A. Mostofi and M.C. Payne
                          ONETEP and CASTEP comparison:
                          •Same basis set
Numerical comparisons     •Same plane wave kinetic energy cut-off
with CASTEP               •Same simulation cells
                          •Same norm-conserving pseudopotentials
                          •Same functional (LDA was used here)
                          •Different CPU and MEMORY scaling
                          (CASTEP is cubic, ONETEP is linear!)

                          Energy difference between neutral
                          /di-ion (zwiterionic) form of
                          peptides

                                     eV               kcal/mol
                 CASTEP           1.21                 28.0
           GLY   ONETEP           1.20                 27.7
                 CASTEP           1.07                 24.7
           PEP   ONETEP           1.08                 24.9
True linear-scaling: Cost per iteration is linear in number of atoms and number of
iterations required for convergence is small and independent of number of atoms

                             GLY                          GLY50


                                                                                                                GLY100




                                             SCF convergence
                                                                                             GLY200
                           1.0E-01                                GLY (10 atoms)

                                                                  GLY50 (353 atoms)

                           1.0E-02                                GLY100 (703 atoms)

                                                                  GLY200 (1403 atoms)
  Energy(Ha) gain / atom




                           1.0E-03
                                                                  NTB (256 atoms)

                                                                  NTB_DEF (516 atoms)
                           1.0E-04


                           1.0E-05


                           1.0E-06                                                             NTB

                           1.0E-07                                                                    NTB_DEF
                                     0   5         10            15       20            25
                                                 SCF iteration
Transferable Ionic Interaction Potentials
        from AIMD (PM & S. Jahn)




  H. Sieber et al, Z. Anorg. Allg. Chemie 622 (1996) 1658
 The Asymmetric Ion Model (AIM)
• extension of shell model
• induction of multipole moments
  – dipoles and quadrupoles (inc. short-range
    induction)
   ions change size and shape
  – spherical breathing, dipolar and quadrupolar
    deformations
• potential with about 20 parameters
        AIM parameterization

1. Produce several different configurations of the
   ionic system (coordination environment, P, T)

2. Calculate ab initio forces, multipoles and stress
   of these configurations using CASTEP/CPMD

3. Optimize potential parameters to reproduce ab
   initio results
Wannier centers for MgO (B2)
   Pressure-driven phase transitions
     (tetrahedral => octahedral)




Increase pressure in “constant-stress” MD simulations
 Zinc Blende to Rocksalt




BEFORE                     AFTER
            Wurtzite to Rocksalt

• Same mechanisms as
  bulk transformations

• Account for change of
  shape and different
  texture of wurtzite &
  blende

				
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posted:10/22/2011
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