DASHMM Accelerated Adaptive Fast Multipole Poisson-Boltzmann Solver on Distributed Memory Architecture
Year: 2019
Communications in Computational Physics, Vol. 25 (2019), Iss. 4 : pp. 1235–1258
Abstract
We present DAFMPB (DASHMM-accelerated Adaptive Fast Multipole Poisson-Boltzmann solver) for rapid evaluation of the electrostatic potentials and forces, and total solvation-free energy in biomolecular systems modeled by the linearized Poisson-Boltzmann (LPB) equation. DAFMPB first reformulates the LPB into a boundary integral equation and then discretizes it using the node-patch scheme [33]. It solves the resulting linear system using GMRES, where it adopts the DASHMM library [14] to accelerate the matrix-vector multiplication in each iteration. DASHMM is built on top of a global address space allowing the user of DAFMPB to operate on both shared and distributed memory computers with modification of their code. This paper is a brief summary of the program, including the algorithm, implementation, installation and usage.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/cicp.OA-2018-0098
Communications in Computational Physics, Vol. 25 (2019), Iss. 4 : pp. 1235–1258
Published online: 2019-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 24
Keywords: Poisson-Boltzmann equation boundary element method DASHMM distributed computing.
-
An Unfitted Finite Element Poisson–Boltzmann Solver with Automatic Resolving of Curved Molecular Surface
Liu, Ziyang | Gui, Sheng | Lu, Benzhuo | Zhang, LinboThe Journal of Physical Chemistry B, Vol. 128 (2024), Iss. 27 P.6463
https://doi.org/10.1021/acs.jpcb.4c01894 [Citations: 0] -
Solving parametric elliptic interface problems via interfaced operator network
Wu, Sidi | Zhu, Aiqing | Tang, Yifa | Lu, BenzhuoJournal of Computational Physics, Vol. 514 (2024), Iss. P.113217
https://doi.org/10.1016/j.jcp.2024.113217 [Citations: 1] -
INN: Interfaced neural networks as an accessible meshless approach for solving interface PDE problems
Wu, Sidi | Lu, BenzhuoJournal of Computational Physics, Vol. 470 (2022), Iss. P.111588
https://doi.org/10.1016/j.jcp.2022.111588 [Citations: 14]