Scalable molecular dynamics on CPU and GPU architectures with NAMD

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...

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Veröffentlicht in:Journal of Chemical Physics 2020-07, Vol.153 (4), p.044130-044130
Hauptverfasser: Phillips, James C., Hardy, David J., Maia, Julio D. C., Stone, John E., Ribeiro, João V., Bernardi, Rafael C., Buch, Ronak, Fiorin, Giacomo, Hénin, Jérôme, Jiang, Wei, McGreevy, Ryan, Melo, Marcelo C. R., Radak, Brian K., Skeel, Robert D., Singharoy, Abhishek, Wang, Yi, Roux, Benoît, Aksimentiev, Aleksei, Luthey-Schulten, Zaida, Kalé, Laxmikant V., Schulten, Klaus, Chipot, Christophe, Tajkhorshid, Emad
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container_issue 4
container_start_page 044130
container_title Journal of Chemical Physics
container_volume 153
creator Phillips, James C.
Hardy, David J.
Maia, Julio D. C.
Stone, John E.
Ribeiro, João V.
Bernardi, Rafael C.
Buch, Ronak
Fiorin, Giacomo
Hénin, Jérôme
Jiang, Wei
McGreevy, Ryan
Melo, Marcelo C. R.
Radak, Brian K.
Skeel, Robert D.
Singharoy, Abhishek
Wang, Yi
Roux, Benoît
Aksimentiev, Aleksei
Luthey-Schulten, Zaida
Kalé, Laxmikant V.
Schulten, Klaus
Chipot, Christophe
Tajkhorshid, Emad
description 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.
doi_str_mv 10.1063/5.0014475
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R.</au><au>Radak, Brian K.</au><au>Skeel, Robert D.</au><au>Singharoy, Abhishek</au><au>Wang, Yi</au><au>Roux, Benoît</au><au>Aksimentiev, Aleksei</au><au>Luthey-Schulten, Zaida</au><au>Kalé, Laxmikant V.</au><au>Schulten, Klaus</au><au>Chipot, Christophe</au><au>Tajkhorshid, Emad</au><aucorp>Argonne National Lab. (ANL), Argonne, IL (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Scalable molecular dynamics on CPU and GPU architectures with NAMD</atitle><jtitle>Journal of Chemical Physics</jtitle><addtitle>J Chem Phys</addtitle><date>2020-07-28</date><risdate>2020</risdate><volume>153</volume><issue>4</issue><spage>044130</spage><epage>044130</epage><pages>044130-044130</pages><issn>0021-9606</issn><eissn>1089-7690</eissn><coden>JCPSA6</coden><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. 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ispartof Journal of Chemical Physics, 2020-07, Vol.153 (4), p.044130-044130
issn 0021-9606
1089-7690
language eng
recordid cdi_scitation_primary_10_1063_5_0014475
source AIP Journals Complete; Alma/SFX Local Collection
subjects Biological Physics
Chemical Sciences
high-performance computing
Molecular dynamics simulation
or physical chemistry
Physics
statistical mechanics
Theoretical and
title Scalable molecular dynamics on CPU and GPU architectures with NAMD
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