TY - JOUR
T1 - NAMD2
T2 - Greater Scalability for Parallel Molecular Dynamics
AU - Kalé, Laxmikant
AU - Skeel, Robert
AU - Bhandarkar, Milind
AU - Brunner, Robert
AU - Gursoy, Attila
AU - Krawetz, Neal
AU - Phillips, James
AU - Shinozaki, Aritomo
AU - Varadarajan, Krishnan
AU - Schulten, Klaus
N1 - Funding Information:
The primary developers of NAMD2 were J. Phillips, A. Shinozaki, R. Brunner, N. Krawetz, M. Bhandarkar, and A. Gursoy. Jesús Izaguirre and Nick Dietz performed regression testing on NAMD2, showing that it produced correct results by comparison with NAMD 1.5. NAMD development is a service of the National Institutes of Health Resource for Macromolecular Modeling and Bioinformatics under the supervision of principal investigators L.V. Kalé, R. Skeel, and K. Schulten. The steered MD module was contributed by Sergei Izrailev. The free energy module was contributed by David Hurwitz from the group of Jan Hermans at the University of North Carolina. The DPMTA and DPME full electrostatics packages were made available by the group of John Board at Duke University. Joshua Yelon tested object-based load balancing on the ASCI Red machine. The developers thank Dorina Kosztin, Sergei Izrailev, and Ferenc Molnar for their early adoption of NAMD2, their patience during the development process, and their contributions to the Initial Applications section of the paper. The work was supported by the National Institutes of Health (under Grant NIH PHS 5 P41 RR05969-04) and the National Science Foundation (under Grants NSF/GCAG BIR 93-18159 and NSF BIR 94-23827 EQ). J.C.P. was supported by a Computational Science Graduate Fellowship from the United States Department of Energy.
PY - 1999/5/1
Y1 - 1999/5/1
N2 - Molecular dynamics programs simulate the behavior of biomolecular systems, leading to understanding of their functions. However, the computational complexity of such simulations is enormous. Parallel machines provide the potential to meet this computational challenge. To harness this potential, it is necessary to develop a scalable program. It is also necessary that the program be easily modified by application-domain programmers. The NAMD2 program presented in this paper seeks to provide these desirable features. It uses spatial decomposition combined with force decomposition to enhance scalability. It uses intelligent periodic load balancing, so as to maximally utilize the available compute power. It is modularly organized, and implemented using Charm++, a parallel C++ dialect, so as to enhance its modifiability. It uses a combination of numerical techniques and algorithms to ensure that energy drifts are minimized, ensuring accuracy in long running calculations. NAMD2 uses a portable run-time framework called Converse that also supports interoperability among multiple parallel paradigms. As a result, different components of applications can be written in the most appropriate parallel paradigms. NAMD2 runs on most parallel machines including workstation clusters and has yielded speedups in excess of 180 on 220 processors. This paper also describes the performance obtained on some benchmark applications.
AB - Molecular dynamics programs simulate the behavior of biomolecular systems, leading to understanding of their functions. However, the computational complexity of such simulations is enormous. Parallel machines provide the potential to meet this computational challenge. To harness this potential, it is necessary to develop a scalable program. It is also necessary that the program be easily modified by application-domain programmers. The NAMD2 program presented in this paper seeks to provide these desirable features. It uses spatial decomposition combined with force decomposition to enhance scalability. It uses intelligent periodic load balancing, so as to maximally utilize the available compute power. It is modularly organized, and implemented using Charm++, a parallel C++ dialect, so as to enhance its modifiability. It uses a combination of numerical techniques and algorithms to ensure that energy drifts are minimized, ensuring accuracy in long running calculations. NAMD2 uses a portable run-time framework called Converse that also supports interoperability among multiple parallel paradigms. As a result, different components of applications can be written in the most appropriate parallel paradigms. NAMD2 runs on most parallel machines including workstation clusters and has yielded speedups in excess of 180 on 220 processors. This paper also describes the performance obtained on some benchmark applications.
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U2 - 10.1006/jcph.1999.6201
DO - 10.1006/jcph.1999.6201
M3 - Article
AN - SCOPUS:0042415783
SN - 0021-9991
VL - 151
SP - 283
EP - 312
JO - Journal of Computational Physics
JF - Journal of Computational Physics
IS - 1
ER -