volume 153 issue 4 pages 44130

Scalable molecular dynamics on CPU and GPU architectures with NAMD

James C. Phillips 1, 2
David J Hardy 1
Julio D C Maia 1
John E Stone 1
João V Ribeiro 1
Rafael C Bernardi 1
Ronak Buch 1, 3
Giacomo Fiorin 4
J Hénin 5
Wei Jiang 1, 6
Ryan McGreevy 1
MARCELO R. S. MELO 1, 7
Brian K Radak 1
Robert Skeel 8
Abhishek Singharoy 9
Yi Wang 10
B. ROUX 11
Aleksei Aksimentiev 1, 12
Zaida Luthey‐Schulten 1, 7
Laxmikant V. Kalé 1, 3
Klaus Schulten 1, 12
Chipot Christophe 1, 12, 13
Emad Tajkhorshid 1, 14
Publication typeJournal Article
Publication date2020-07-28
scimago Q1
wos Q2
SJR0.819
CiteScore5.3
Impact factor3.1
ISSN00219606, 10897690
PubMed ID:  32752662
Physical and Theoretical Chemistry
General Physics and Astronomy
Abstract

NAMD is a molecular dynamics program designed for high-performance simulations of very large biological objects on CPU- and GPU-based architectures. NAMD offers scalable performance on petascale parallel supercomputers consisting of hundreds of thousands of cores, as well as on inexpensive commodity clusters commonly found in academic environments. It is written in C++ and leans on Charm++ parallel objects for optimal performance on low-latency architectures. NAMD is a versatile, multipurpose code that gathers state-of-the-art algorithms to carry out simulations in apt thermodynamic ensembles, using the widely popular CHARMM, AMBER, OPLS, and GROMOS biomolecular force fields. Here, we review the main features of NAMD that allow both equilibrium and enhanced-sampling molecular dynamics simulations with numerical efficiency. We describe the underlying concepts utilized by NAMD and their implementation, most notably for handling long-range electrostatics; controlling the temperature, pressure, and pH; applying external potentials on tailored grids; leveraging massively parallel resources in multiple-copy simulations; and hybrid quantum-mechanical/molecular-mechanical descriptions. We detail the variety of options offered by NAMD for enhanced-sampling simulations aimed at determining free-energy differences of either alchemical or geometrical transformations and outline their applicability to specific problems. Last, we discuss the roadmap for the development of NAMD and our current efforts toward achieving optimal performance on GPU-based architectures, for pushing back the limitations that have prevented biologically realistic billion-atom objects to be fruitfully simulated, and for making large-scale simulations less expensive and easier to set up, run, and analyze. NAMD is distributed free of charge with its source code at www.ks.uiuc.edu.

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GOST Copy
Phillips J. C. et al. Scalable molecular dynamics on CPU and GPU architectures with NAMD // Journal of Chemical Physics. 2020. Vol. 153. No. 4. p. 44130.
GOST all authors (up to 50) Copy
Phillips J. C., Hardy D. J., Maia J. D. C., Stone J. E., Ribeiro J. V., Bernardi R. C., Buch R., Fiorin G., Hénin J., Jiang W., McGreevy R., MELO M. R. S., Radak B. K., Skeel R., Singharoy A., Wang Y., ROUX B., Aksimentiev A., Luthey‐Schulten Z., Kalé L. V., Schulten K., Christophe C., Tajkhorshid E. Scalable molecular dynamics on CPU and GPU architectures with NAMD // Journal of Chemical Physics. 2020. Vol. 153. No. 4. p. 44130.
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1063/5.0014475
UR - https://doi.org/10.1063/5.0014475
TI - Scalable molecular dynamics on CPU and GPU architectures with NAMD
T2 - Journal of Chemical Physics
AU - Phillips, James C.
AU - Hardy, David J
AU - Maia, Julio D C
AU - Stone, John E
AU - Ribeiro, João V
AU - Bernardi, Rafael C
AU - Buch, Ronak
AU - Fiorin, Giacomo
AU - Hénin, J
AU - Jiang, Wei
AU - McGreevy, Ryan
AU - MELO, MARCELO R. S.
AU - Radak, Brian K
AU - Skeel, Robert
AU - Singharoy, Abhishek
AU - Wang, Yi
AU - ROUX, B.
AU - Aksimentiev, Aleksei
AU - Luthey‐Schulten, Zaida
AU - Kalé, Laxmikant V.
AU - Schulten, Klaus
AU - Christophe, Chipot
AU - Tajkhorshid, Emad
PY - 2020
DA - 2020/07/28
PB - AIP Publishing
SP - 44130
IS - 4
VL - 153
PMID - 32752662
SN - 0021-9606
SN - 1089-7690
ER -
BibTex |
Cite this
BibTex (up to 50 authors) Copy
@article{2020_Phillips,
author = {James C. Phillips and David J Hardy and Julio D C Maia and John E Stone and João V Ribeiro and Rafael C Bernardi and Ronak Buch and Giacomo Fiorin and J Hénin and Wei Jiang and Ryan McGreevy and MARCELO R. S. MELO and Brian K Radak and Robert Skeel and Abhishek Singharoy and Yi Wang and B. ROUX and Aleksei Aksimentiev and Zaida Luthey‐Schulten and Laxmikant V. Kalé and Klaus Schulten and Chipot Christophe and Emad Tajkhorshid},
title = {Scalable molecular dynamics on CPU and GPU architectures with NAMD},
journal = {Journal of Chemical Physics},
year = {2020},
volume = {153},
publisher = {AIP Publishing},
month = {jul},
url = {https://doi.org/10.1063/5.0014475},
number = {4},
pages = {44130},
doi = {10.1063/5.0014475}
}
MLA
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MLA Copy
Phillips, James C., et al. “Scalable molecular dynamics on CPU and GPU architectures with NAMD.” Journal of Chemical Physics, vol. 153, no. 4, Jul. 2020, p. 44130. https://doi.org/10.1063/5.0014475.
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