NDLI: FENZI: GPU-Enabled Molecular Dynamics Simulations of Large Membrane Regions Based on the CHARMM Force Field and PME

Content Provider	IEEE Xplore Digital Library
Author	Ganesan, N. Taufer, M. Bauer, B. Patel, S.
Copyright Year	2011
Abstract	When studying membrane-bound protein receptors, it is necessary to move beyond the current state-of-the-art simulations that only consider small membrane patches and implicit solvent. Limits of traditional computer platforms negatively impact the model's level of realism and the computational scales achievable. On the other hand, multi-core platforms such as GPUs offer the possibility to span length scales in membrane simulations much larger and with higher resolutions than before. To this end, this paper presents the design and implementation of an advanced GPU algorithm for Molecular Dynamics (MD) simulations of large membrane regions in the NVT, NVE, and NPT ensembles using explicit solvent and Particle Mesh Ewald (PME) method for treating the conditionally-convergent electrostatic component of the classical force field. A key component of our algorithm is the redesign of the traditional PME method to better fit on the multithreading GPU architecture. This has been considered a fundamentally hard problem in the molecular dynamics community working on massively multithreaded architecture. Our algorithm is integrated in the code FENZI (textit{yun dong de FEN ZI} in Mandarin or textit{moving molecules} in English). The paper analyzes both the performance and accuracy of large-scale GPU-enabled simulations of membranes using FENZI, showing how our code can enable multi-nanosecond MD simulations per day, even when using PME.
Starting Page	472
Ending Page	480
File Size	982027
Page Count	9
File Format	PDF
ISBN	9781612844251
ISSN	15302075
DOI	10.1109/IPDPS.2011.187
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computational modeling Biological system modeling Force Lattices Computer architecture Biomembranes Graphics processing unit
Content Type	Text
Resource Type	Article

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