Evidence map›Paper›PMID 30147116›Full record

ArticleComputer physics communications2018

RPYFMM: Parallel Adaptive Fast Multipole Method for Rotne-Prager-Yamakawa Tensor in Biomolecular Hydrodynamics Simulations.

W Guan, X Cheng, J Huang, G Huber, W Li, J A McCammon, B Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computer physics communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

1 citing paper in PubMed.

  1. 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

7 authors.

W GuanDepartment of Mathematics, University of North Carolina, Chapel Hill, NC 27599-3250, USA.
X ChengMedicinal Chemistry and Pharmacognosy, College of Pharmacy, Ohio State University, Columbus, OH 43210, USA.
J HuangDepartment of Mathematics, University of North Carolina, Chapel Hill, NC 27599-3250, USA.
G HuberDepartment of Chemistry and Biochemistry and Department of Pharmacology, University of California at San Diego, La Jolla, CA 92093-0365.
W LiSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo, Shandong, China.
J A McCammonDepartment of Chemistry and Biochemistry and Department of Pharmacology, University of California at San Diego, La Jolla, CA 92093-0365.
B ZhangCenter for Research in Extreme Scale Technologies, School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, 47404, USA.

Funding

THEORY OF BIOMOLECULAR DIFFUSIONR01GM031749 · NIGMS · UNIVERSITY OF HOUSTON · PI HUBER, GARY ALEXANDER, MCCAMMON, JAMES ANDREW · 1985 to 2022
$7.8M
NIGMS NIH HHS R01 GM031749
6 · The paper itself

Abstract

RPYFMM is a software package for the efficient evaluation of the potential field governed by the Rotne-Prager-Yamakawa (RPY) tensor interactions in biomolecular hydrodynamics simulations. In our algorithm, the RPY tensor is decomposed as a linear combination of four Laplace interactions, each of which is evaluated using the adaptive fast multipole method (FMM) [1] where the exponential expansions are applied to diagonalize the multipole-to-local translation operators. RPYFMM offers a unified execution on both shared and distributed memory computers by leveraging the DASHMM library [2, 3]. Preliminary numerical results show that the interactions for a molecular system of 15 million particles (beads) can be computed within one second on a Cray XC30 cluster using 12, 288 cores, while achieving approximately 54% strong-scaling efficiency.

Indexed as

Brownian dynamicsDASHMMFast multipole methodHydrodynamics interactionsRotne-Prager-Yamakawa tensor

Identifiers

PMID30147116
PMCPMC6107314

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Registered trials

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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.