A divide-and-conquer/cellular-decomposition framework for million-to-billion atom simulations of chemical reactions

Aiichiro Nakano, Rajiv K. Kalia, Ken ichi Nomura, Ashish Sharma, Priya Vashishta, Fuyuki Shimojo, Adri Van Duin, William A. Goddard, Rupak Biswas, Deepak Srivastava

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Abstract

To enable large-scale atomistic simulations of material processes involving chemical reactions, we have designed linear-scaling molecular dynamics (MD) algorithms based on an embedded divide-and-conquer (EDC) framework: first principles-based fast reactive force-field (F-ReaxFF) MD; and quantum-mechanical MD in the framework of the density functional theory (DFT) on adaptive multigrids. To map these O(N) algorithms onto parallel computers with deep memory hierarchies, we have developed a tunable hierarchical cellular-decomposition (THCD) framework, which achieves performance tunability through a hierarchy of parameterized cell data/computation structures and adaptive load balancing through wavelet-based computational-space decomposition. Benchmark tests on 1920 Itanium2 processors of the NASA Columbia supercomputer have achieved unprecedented scales of quantum-mechanically accurate and well validated, chemically reactive atomistic simulations-0.56 billion-atom F-ReaxFF MD and 1.4 million-atom (0.12 trillion grid points) EDC-DFT MD-in addition to 18.9 billion-atom non reactive space-time multiresolution MD. The EDC and THCD frameworks expose maximal data localities, and consequently the isogranular parallel efficiency on 1920 processors is as high as 0.953. Chemically reactive MD simulations have been applied to shock-initiated detonation of energetic materials and stress-induced bond breaking in ceramics in corrosive environments.

Original languageEnglish (US)
Pages (from-to)642-652
Number of pages11
JournalComputational Materials Science
Volume38
Issue number4
DOIs
StatePublished - Feb 1 2007

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Chemistry(all)
  • Materials Science(all)
  • Mechanics of Materials
  • Physics and Astronomy(all)
  • Computational Mathematics

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    Nakano, A., Kalia, R. K., Nomura, K. I., Sharma, A., Vashishta, P., Shimojo, F., Van Duin, A., Goddard, W. A., Biswas, R., & Srivastava, D. (2007). A divide-and-conquer/cellular-decomposition framework for million-to-billion atom simulations of chemical reactions. Computational Materials Science, 38(4), 642-652. https://doi.org/10.1016/j.commatsci.2006.04.012