Singapore-2013

1. Singapore-2013 “High-performance computational GPU-stand for teaching undergraduate and graduate students the basics of quantum-mechanical calculations“ Sergey Seriy “Komsomolsk-on-Amur State Technical University”681013, Russia, Komsomolsk-on-Amur city, Lenina-27email: gray@knastu.ru, uru.40@mail.ru,only_nina@mail.ru

2. Overview • Teaching of classical and DFT “ab-initio” calculations( samples of bulk, slab, particle structures, thin-film, alloys, etc) • Using Atomistic Simulation Environment (ASE) and GPU-based software for calculations • ASE universality: electronic structure codes + LAMMPS or ABINIT or CP2K or GPAW, with GPU-support • ASE exercises: tests of defect energies, heats of formation, elastic constants, etc. • Conclusion

3. Main Goal: “Teaching for calculate basic structural properties of single crystals, formationenergies of defects, and structural and elastic properties of simple nanostructures, using GPU (NVidia, ATI and both)” • Need to learn formats of input parameter files, atomicconguration files, and output files of • ab-initio code (CP2K, Abinit, GPAW) • classical code (LAMMPS) • Need to create atomic congurations for • single crystal structures, crystallic compounds, point defects(vacancies, interstitials, substitutions), planar defects (varyingsurfaces, stacking faults), and strained structures

4. Need a tool applicable to quickly evaluate basic properties fromclassical potentials and ab-initio methods. • Ideally, a single universal tool would be able to • create basic atomic congurations and manipulate them • serve these atomistic congurations as inputs to a variety ofmethods/simulation codes and obtain energies • Anything like that available? • Atomistic Simulation Environment (ASE)

5. Atomistic Simulation Environment (ASE) v. 3.0 • universal Python interface to many DFT codes (calculators), with visualization, simple GUI, documentation, and tutorials • creates molecules, crystal structures, surfaces, nanotubes, analyzes symmetry and spacegroups • provides support for Equation of state, structure optimization,dissociation, diusion, constrains, NEB, vibration analysis, phonon calculations, infrared intensities, molecular dynamics, STM, electron transport, …

6. -- and CP2K – DFT-based molecular dynamics code (consist in old version ASE 2.0)

15. Conclusions • ASE provides a universal interface to many electronic-structurecodes • ASE interface for LAMMPS, ABINIT and CP2K on GPU was utilized in learning students • Following the LAMMPS example, ASE can provide support toother classical and “ab-initio” codes • ASE simplies and increases eciency of atomistic simulation learning

19. Multicore, CPU & GPU Core i7 (45nm) GTX285 (55nm)

27. Mathematical modeling: nano-coatings for cutting tools

28. VMD – “Visual Molecular Dynamics” • Visualization and analysis of molecular dynamics simulations, sequence data, volumetric data, quantum chemistry simulations, particle systems, … • User extensible with scripting and plugins

29. GPU Acceleration in VMD Electrostatic field calculation, ion placement: factor of 20x to 44x faster Molecular orbital calculation and display: factor of 120x faster Imaging of gas migration pathways in proteins with implicit ligand sampling: factor of 20x to 30x faster

30. Mesoscale modelling on CUDA:Fluid Dynamics • Double precision • 384 x 384 x 192 grid (max that fits in 4GB) • Vertical slice of temperature at y=0 • Transition from stratified (left) to turbulent (right) • Regime depends on Rayleigh number: Ra = gαΔT/κν • 8.5x speedup versus Fortran code running on 8-core 2.5 GHz Xeon

31. Thank you for your attention