1. Mid-Year Review Template March 2, 2010 Purdue University

2. Reactive Atomistics Metin Aktulga and Ananth Grama

3. 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.

4. 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.

5. Continuing Workplan Benchmark scalability on larger configurations
Address known scalability bottlenecks (qEq solver)
Fully integrate into LAMMPS
Continue development of FFOpt

6. 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

7. Purdue ReaxFF Results:
Approximately 10 times faster than competing Reax code
10-20 times smaller memory footprint and adaptive to resource and problem requirements

8. Purdue Reax Y. Park, H. Aktulga, A. Grama, A. Strachan
“Strain relaxation in Si/Ge/Si nanoscale bars from MD simulations”
J Appl Phys 106, (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. Pandit
Oxidative Damage in Lipid Bilayers: A Reactive Molecular Dynamics Study, Biophys. Soc. (2010)

9. 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
GMRES+ diag
CG/ilu(10−2)
GMRES /ilu(10−2)
ILU-based preconditioners 3 x better performance!
QEq now takes as low as 6-7% of total time!

10. 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

11. Purdue Parallel Reax Performance
Bulk water system (6540 atoms):
executable cores time per step QEq time per step
SerialReax (icc -fast)
ParallelReax(icc -O3)
Bilayer system (56800 atoms):
SerialReax (icc -fast)
ParallelReax(icc -O3)
Performance degrades mostly due to parallel QEq solver
Working with Dr Manguoglu on SPIKE-based QEq solver

12. Scaling Results

13. 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