Mid-Year Review Template

March 2, 2010Purdue University

Reactive AtomisticsMetin Aktulga and Ananth Grama

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Accomplishments

• Purdue ReaxFF represents a unique capability – simulating reactive systems with 106 atoms and beyond, at high accuracies.

• The speed and scale of such simulations is well beyond competing implementations.

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Accomplishments• V 2.0 of Serial ReaxFF Code Released

• V 1.0 of Parallel ReaxFF Code Released

• Initial third-party benchmarking (Goddard et al.) shows Purdue Reax is approx. 10 x faster than competing/ collaborating implementation

• Initial third-party benchmarking shows parallel version to be stable and scalable to 1K cores.

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Continuing Workplan

• Benchmark scalability on larger configurations

• Address known scalability bottlenecks (qEq solver)

• Fully integrate into LAMMPS

• Continue development of FFOpt

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Purdue ReaxFF

• Optimizations in every part of the code:• efficient generation of nbrs & intrs lists• completely dynamic memory management for

all lists• fast computation of bond-related forces• computation of van der Waals & Coulomb

interactions with cubic spline interpolations• efficient QEq solver: GMRES+ILU-based

preconditioner

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Purdue ReaxFF

• Results:• Approximately 10 times faster than competing

Reax code• 10-20 times smaller memory footprint and

adaptive to resource and problem requirements

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Purdue Reax

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Y. Park, H. Aktulga, A. Grama, A. Strachan“Strain relaxation in Si/Ge/Si nanoscale bars from MD simulations”J Appl Phys 106, 034304 (2009)J. Fogarty, H. Aktulga, A. van Duin, A. Grama, S. Pandit“A Reactive Simulation of the Silica-Water Interface”, J Comp Phys (2010)J. Fogarty, H. Aktulga, A. Grama, and S. PanditOxidative Damage in Lipid Bilayers: A Reactive Molecular Dynamics Study, Biophys. Soc. (2010)

Purdue Reax: Performance

• Reference 6540 atom bulk water system• QEq tolerance = 10−6 (refactor every 100 steps)

• QEq tolerance = 10−10 (refactor every 30 steps)

tol=10−6 tol=10−10

solver matvecs time matvecs time

CG + diag. 31 0.18 95 0.54

GMRES+ diag. 18 0.11 81 0.49

CG/ilu(10−2) 9 0.06 18 0.13

GMRES /ilu(10−2) 6 0.04 15 0.11

• ILU-based preconditioners 3 x better performance!• QEq now takes as low as 6-7% of total time!

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Purdue Parallel Reax

• Inherits major part of the code from SerialReax• slower QEq solver: CG + diagonal

preconditioner• larger memory footprint: conservative

allocation + communication buffers• internal release: Feb 16, 2010• will be used in PRISM metal-dielectric contact

simulations

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Purdue Parallel Reax Performance

Bulk water system (6540 atoms):executable cores time per step QEq time per step

SerialReax (icc -fast) 1 0.74 0.12

ParallelReax(icc -O3) 1 1.46 0.55

Bilayer system (56800 atoms):

executable cores time per step QEq time per step

SerialReax (icc -fast) 1 7.76 1.34

ParallelReax(icc -O3) 1 13.30 6.30

• Performance degrades mostly due to parallel QEq solver• Working with Dr Manguoglu on SPIKE-based QEq solver

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Scaling Results

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Integration Efforts

• Initial qEq integration into LAMMPS needs to be redone• Changes to LAMMPS interface• Changes to Purdue Reax

• Integration of Purdue Reax 2.0 into LAMMPS

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