Evidence map›Paper›PMID 22039358›Full record

ArticleJournal of chemical theory and computation2010

Multi-Level Ewald: A hybrid multigrid / Fast Fourier Transform approach to the electrostatic particle-mesh problem.

David S Cerutti, David A Case

Abstract read
In one paragraph

Article in Journal of chemical theory and computation, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Quantum mechanical force fields for condensed phase molecular simulations.Journal of physics. Condensed matter : an Institute of Physics journal · 2017
    Article
  4. Article
  5. Article
  6. Multipolar Ewald methods, 1: theory, accuracy, and performance.Journal of chemical theory and computation · 2015
    Article
  7. Review
  8. Progress in developing Poisson-Boltzmann equation solvers.Molecular based mathematical biology · 2013
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

David S CeruttiDepartment of Chemistry and Chemical Biology, and BioMaPS Institute, Rutgers University, 610 Taylor Road, Piscataway, NJ 08854-8066.
David A Case

Funding

WEB BASED DOCUMENTATION &TUTORIALS FOR YAMMPP41RR012255 · NCRR · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI BROOKS, CHARLES L · 1997 to 2009
$10.4M
NCRR NIH HHS P41 RR012255
6 · The paper itself

Abstract

We present a new method for decomposing the one convolution required by standard Particle-Particle Particle-Mesh (P(3)M) electrostatic methods into a series of convolutions over slab-shaped subregions of the original simulation cell. Most of the convolutions derive data from separate regions of the cell and can thus be computed independently via FFTs, in some cases with a small amount of zero padding so that the results of these sub-problems may be reunited with minimal error. A single convolution over the entire cell is also performed, but using a much coarser mesh than the original problem would have required. This "Multi-Level Ewald" (MLE) method therefore requires moderately more FFT work plus the tasks of interpolating between different sizes of mesh and accumulating the results from neighboring sub-problems, but we show that the added expense can be less than 10% of the total simulation cost. We implement MLE as an approximation to the Smooth Particle Mesh Ewald (SPME) style of P(3)M, and identify a number of tunable parameters in MLE. With reasonable settings pertaining to the degree of overlap between the various sub-problems and the accuracy of interpolation between meshes, the errors obtained by MLE can be smaller than those obtained in molecular simulations with typical SPME settings. We compare simulations of a box of water molecules performed with MLE and SPME, and show that the energy conservation, structural, and dynamical properties of the system are more affected by the accuracy of the SPME calculation itself than by the additional MLE approximation. We anticipate that the MLE method's ability to break a single convolution into many independent sub-problems will be useful for extending the parallel scaling of molecular simulations.

Identifiers

PMID22039358
PMCPMC3202610

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.