“High-performance computational GPU-stand for teaching undergraduate and graduate students the basics of quantum-mechanical calculations“

“Komsomolsk-on-Amur State Technical University”

681013, Russia, Komsomolsk-on-Amur city, Lenina-27

email: gray@knastu.ru, uru.40@mail.ru,only_nina@mail.ru

Singapore-2013

Sergey Seriy

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

Main Goal:

“Teaching for calculate basic structural properties of single crystals, formation energies of defects, and structural and elastic properties of simple nanostructures, using GPU (NVidia, ATI and both)”

Need to learn formats of input parameter files, atomic conguration 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 (varying surfaces, stacking faults), and strained structures

Need a tool applicable to quickly evaluate basic properties from classical 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 of methods/simulation codes and obtain energies

Anything like that available?

Atomistic Simulation Environment (ASE)

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, …

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

Conclusions

ASE provides a universal interface to many electronic-structure codes

ASE interface for LAMMPS, ABINIT and CP2K on GPU was utilized in learning students

Following the LAMMPS example, ASE can provide support to other classical and “ab-initio” codes

ASE simplies and increases eciency of atomistic simulation learning

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Multicore, CPU & GPU

Specifications Core i7 960 GTX285

Processing Elements 4 cores, 4 way SIMD@3.2 GHz

30 cores, 8 way SIMD@1.5 GHz

Resident Strands/Threads

(max)

4 cores, 2 threads, 4 way SIMD:

32 strands

30 cores, 32 SIMD vectors, 32 way

SIMD:30720 threads

SP GFLOP/s 102 1080

Memory Bandwidth 25.6 GB/s 159 GB/s

Register File - 1.875 MB

Local Store - 480 kB

Core i7 (45nm)

GTX285 (55nm)

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Mathematical modeling: nano-coatings for cutting tools

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

Molecular orbital

calculation and display:

factor of 120x fasterImaging of gas migration pathways in proteins with implicit ligand sampling:

factor of 20x to 30x faster

GPU Acceleration in VMD

Electrostatic field

calculation, ion placement:

factor of 20x to 44x faster

Mesoscale modelling on CUDA:Fluid Dynamics

Double precision384 x 384 x 192 grid (max that fits in 4GB)Vertical slice of temperature at y=0Transition from stratified (left) to turbulent (right)Regime depends on Rayleigh number: Ra = gαΔT/κν8.5x speedup versus Fortran code running on 8-core 2.5 GHz Xeon

Thank you for your attention