MDSIMAID: Automatic parameter optimization in fast electrostatic algorithms

被引：5

作者：

Crocker, MS

Hampton, SS

Matthey, T

Izaguirre, JA ^{[1
]}

机构：

[1] Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46556 USA

[2] Univ Bergen, Parallab, N-5020 Bergen, Norway

[3] Univ Bergen, Bergen Ctr Computat Sci, N-5020 Bergen, Norway

来源：

JOURNAL OF COMPUTATIONAL CHEMISTRY | 2005年 / 26卷 / 10期

关键词：

automatic parameter optimization; fast electrostatic algorithms;

D O I：

10.1002/jcc.20240

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

MDSIMAID is a recommender system that optimizes parallel Particle Mesh Ewald (PME) and both sequential and parallel multigrid (MG) summation fast electrostatic solvers. MDSIMAID optimizes the running time or parallel scalability of these methods within a given error tolerance. MDSIMAID performs a run time constrained search on the parameter space of each method starting from semiempirical performance models. Recommended parameters are presented to the user. MDSIMAID'S optimization of MG leads to configurations that are up to 14 times faster or 17 times more accurate than published recommendations. Optimization of PME can improve its parallel scalability, making it run twice as fast in parallel in our tests. MDSIMAID and its Python source code are accessible through a Web portal located at http://mdsimaid.cse.nd.edu. (c) 2005 Wiley Periodicals, Inc.

引用

页码：1021 / 1031

页数：11

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