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Volume 25, Issue 4
DASHMM Accelerated Adaptive Fast Multipole Poisson-Boltzmann Solver on Distributed Memory Architecture

Bo Zhang, Jackson DeBuhr, Drake Niedzielski, Silvio Mayolo, Benzhuo Lu & Thomas Sterling

Commun. Comput. Phys., 25 (2019), pp. 1235-1258.

Published online: 2018-12

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  • 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.

  • AMS Subject Headings

45B05, 31C20, 92C05, 68N19

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{CiCP-25-1235, author = {Bo Zhang, Jackson DeBuhr, Drake Niedzielski, Silvio Mayolo, Benzhuo Lu and Thomas Sterling}, title = {DASHMM Accelerated Adaptive Fast Multipole Poisson-Boltzmann Solver on Distributed Memory Architecture}, journal = {Communications in Computational Physics}, year = {2018}, volume = {25}, number = {4}, pages = {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.

}, issn = {1991-7120}, doi = {https://doi.org/10.4208/cicp.OA-2018-0098}, url = {http://global-sci.org/intro/article_detail/cicp/12897.html} }
TY - JOUR T1 - DASHMM Accelerated Adaptive Fast Multipole Poisson-Boltzmann Solver on Distributed Memory Architecture AU - Bo Zhang, Jackson DeBuhr, Drake Niedzielski, Silvio Mayolo, Benzhuo Lu & Thomas Sterling JO - Communications in Computational Physics VL - 4 SP - 1235 EP - 1258 PY - 2018 DA - 2018/12 SN - 25 DO - http://doi.org/10.4208/cicp.OA-2018-0098 UR - https://global-sci.org/intro/article_detail/cicp/12897.html KW - Poisson-Boltzmann equation, boundary element method, DASHMM, distributed computing. AB -

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.

Bo Zhang, Jackson DeBuhr, Drake Niedzielski, Silvio Mayolo, Benzhuo Lu and Thomas Sterling. (2018). DASHMM Accelerated Adaptive Fast Multipole Poisson-Boltzmann Solver on Distributed Memory Architecture. Communications in Computational Physics. 25 (4). 1235-1258. doi:10.4208/cicp.OA-2018-0098
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