Mathematical and Numerical Aspects of the Adaptive Fast Multipole Poisson-Boltzmann Solver

Zhang, Bo; Lu, Benzhuo; Cheng, Xiaolin; Huang, Jingfang; Pitsianis, Nikos P.; Sun, Xiaobai; McCammon, J. Andrew

doi:10.4208/cicp.210711.111111s

Mathematical and Numerical Aspects of the Adaptive Fast Multipole Poisson-Boltzmann Solver

Journal Article · Mon Dec 31 23:00:00 EST 2012 · Communications in Computational Physics

DOI:https://doi.org/10.4208/cicp.210711.111111s· OSTI ID:1376302

Zhang, Bo ^[1]; Lu, Benzhuo ^[2]; Cheng, Xiaolin ^[3]; Huang, Jingfang ^[4]; Pitsianis, Nikos P. ^[5]; Sun, Xiaobai ^[1]; McCammon, J. Andrew ^[6]

Duke Univ., Durham, NC (United States). Dept. of Computer Science
Chinese Academy of Sciences (CAS), Beijing (China). Inst. of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Science
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Molecular Biophysics
Univ. of North Carolina, Chapel Hill, NC (United States). Dept. of Mathematics
Duke Univ., Durham, NC (United States). Dept. of Computer Science; Aristotle Univ., Thessaloniki (Greece). Dept. of Electrical and Computer Engineering
Howard Hughes Medical Inst., Chevy Chase, MD (United States). Dept. of Pharmacology; Univ. of California, San Diego, CA (United States)

This paper summarizes the mathematical and numerical theories and computational elements of the adaptive fast multipole Poisson-Boltzmann (AFMPB) solver. We introduce and discuss the following components in order: the Poisson-Boltzmann model, boundary integral equation reformulation, surface mesh generation, the nodepatch discretization approach, Krylov iterative methods, the new version of fast multipole methods (FMMs), and a dynamic prioritization technique for scheduling parallel operations. For each component, we also remark on feasible approaches for further improvements in efficiency, accuracy and applicability of the AFMPB solver to large-scale long-time molecular dynamics simulations. Lastly, the potential of the solver is demonstrated with preliminary numerical results.

View Accepted Manuscript (DOE)

Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE; National Science Foundation (NSF); National Institutes of Health (NIH); Chinese Academy of Sciences

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1376302

Journal Information:: Communications in Computational Physics, Journal Name: Communications in Computational Physics Journal Issue: 01 Vol. 13; ISSN 1815-2406; ISSN applab

Publisher:: Global Science PressCopyright Statement

Country of Publication:: United States

Language:: English

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Mathematical and Numerical Aspects of the Adaptive Fast Multipole Poisson-Boltzmann Solver

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