- 作者：Benzhuo Lu ; Xiaolin Cheng ; Jingfang Huang ; J. Andrew McCammon
- 关键词：Poisson&ndash ; Boltzmann equation ; Boundary integral equation ; Node-patch method ; Krylov subspace methods ; Fast multipole methods ; Diagonal translations
- 刊名：Computer Physics Communications
- 出版年：2013
- 出版时间：November, 2013
- 年：2013
- 卷：184
- 期：11
- 页码：2618-2619
- 全文大小：318 K
New version program summary
Program title: AFMPB
Catalogue identifier: AEGB_v1_1
Program summary URL:
Program obtainable from: CPC Program Library, Queen¡¯s University, Belfast, N. Ireland
Licensing provisions: GNU General Public License, version 2
No. of lines in distributed program, including test data, etc.: 440784
No. of bytes in distributed program, including test data, etc.: 8187139
Distribution format: tar.gz
Programming language: Fortran
Computer: Any
Operating system: Any
RAM: Depends on the size of the discretized biomolecular system
Classification: 3
External routines: Pre- and post-processing tools are required for generating the boundary elements and for visualization. Users can use MSMS () for pre-processing, and VMD () for visualization. Sub-programs included: An iterative Krylov subspace solvers package from SPARSKIT by Yousef Saad (), and the fast multipole methods subroutines from FMMSuite ().
Catalogue identifier of previous version: AEGB_v1_0
Journal reference of previous version: Comput. Phys. Comm. 181 (2010) 1150
Does the new version supersede the previous version?: Yes
Nature of problem: Numerical solution of the linearized Poisson-Boltzmann equation that describes electrostatic interactions of molecular systems in ionic solutions.
Solution method: A novel node-patch scheme is used to discretize the well-conditioned boundary integral equation formulation of the linearized Poisson-Boltzmann equation. Various Krylov subspace solvers can be subsequently applied to solve the resulting linear system, with a bounded number of iterations independent of the number of discretized unknowns. The matrix-vector multiplication at each iteration is accelerated by the adaptive new versions of fast multipole methods. The AFMPB solver requires other stand-alone pre-processing tools for boundary mesh generation, post-processing tools for data analysis and visualization, and can be conveniently coupled with different time stepping methods for dynamics simulation.
Reasons for new version: Some bugs are fixed in the new version.
Summary of revisions:
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The type definition of ippt1 in line 88 of FBEM/bempb.f and line 32 of FBEM/closecoef.f is changed from real *8 to integer*4, and a similar change is made for ippt in line 105 of FBEM/solvpb.f and in line 32 of FBEM/closecoef.f.
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In FBEM/elmgeom.f, line 239 ¡°ELSEIF (meshfmt.EQ.1.OR. meshfmt.EQ. 4.OR. meshfmt.EQ.5) THEN¡± is changed to ¡°ELSEIF (meshfmt.EQ.1.OR. meshfmt.EQ. 4) THEN¡±, line 478 ¡°KJ=IDFCL(K)+J-1¡± is changed to ¡°i=IDFCL(K)+J-1¡±, line 479 ¡°KJ=NE(KJ)¡± is changed to ¡°KJ=NE(i)¡±, line 480 ¡°KJ1=NE(KJ+1)¡± is changed to ¡°KJ1=NE(i+1)¡±, and line 647 ¡°?????STOP¡± is changed to ¡°c?????STOP¡±.
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Five subroutines in FMM part (syukadap.f, syukdn.f, slapadap.f, slapdn.f, and treeadap.f) are substituted with the new ones in the new version.
Unusual features: Most of the codes are in Fortran77 style. Memory allocation functions from Fortran90 and above are used in a few subroutines.
Additional comments: The current version of the codes is designed and written for single core/processor desktop machines. Check for updates and changes.
Running time: The running time varies with the number of discretized elements () in the system and their distributions. In most cases, it scales linearly as a function of .