Convergence and time to solution of PyGBe with lysozyme molecule

This file bundle includes data, figures and plotting scripts of convergence and time-to-solution versus error for PyGBe and APBS using a lysozyme molecule. The errors were calculated with respect to the corresponding extrapolated values (obtained from Richardson extrapolation).
This result is part of the paper:
—"A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers", Christopher D. Cooper, Jaydeep P. Bardhan, L. A. Barba. Comput. Phys. Comm., 185(3):720–729 (March 2014). 10.1016/j.cpc.2013.10.028 // Preprint arXiv:1309.4018

PyGBe solves biomolecular electrostatics problems using an implicit-solvent model (Poisson-Boltzmann) and it uses GPU hardware for fast execution. It is written in Python, PyCUDA and CUDA.
More information about the PyGBe code in:
—Validation of the PyGBe code for Poisson-Boltzmann equation with boundary element methods. Christopher Cooper, Lorena A. Barba. figshare.http://dx.doi.org/10.6084/m9.figshare.154331

Acknowledgement:This research is made possible by support from the Office of Naval Research, Applied Computational Analysis Program, N00014-11-1-0356. LAB also acknowledges support from NSF CAREER award OCI-1149784.

本文件包包含了使用溶菌酶分子进行 PyGBe 和 APBS 收敛性以及求解时间与误差对比的数据、图表及绘图脚本。误差计算是以对应外推值（由 Richardson 外推法获得）为基准。此结果收录于以下论文中：——“基于 Python、GPU 和边界元方法求解生物分子静电学问题的生物分子静电学求解器”，Christopher D. Cooper，Jaydeep P. Bardhan，L. A. Barba. 计算物理通信，第 185 卷第 3 期：720–729（2014 年 3 月）。10.1016/j.cpc.2013.10.028 // 预印本 arXiv:1309.4018

PyGBe 通过隐式溶剂模型（泊松-玻尔兹曼方程）求解生物分子静电学问题，并利用 GPU 硬件加速执行。该软件使用 Python、PyCUDA 和 CUDA 编写。

更多关于 PyGBe 代码的信息请参阅：——Poisson-Boltzmann 方程边界元方法的 PyGBe 代码验证。Christopher Cooper，Lorena A. Barba. figshare.http://dx.doi.org/10.6084/m9.figshare.154331

致谢：本研究的开展得益于海军研究办公室应用计算分析计划的支持，合同号 N00014-11-1-0356。实验室还感谢 NSF CAREER 奖励（OCI-1149784）的支持。