Scalable Molecular Dynamics for Large Biomolecular Systems

We present an optimized parallelization scheme for molecular dynamics simulations of large biomolecular systems, implemented in the production-quality molecular dynamics program NAMD. With an object-based hybrid force and spatial decomposition scheme, and an aggressive measurement-based predictive load balancing framework, we have attained speeds and speedups that are much higher than any reported in literature so far. The paper first summarizes the broad methodology we are pursuing, and the basic parallelization scheme we used. It then describes the optimizations that were instrumental in increasing performance, and presents performance results on benchmark simulations.

[1]  L Wang,et al.  The early stage of folding of villin headpiece subdomain observed in a 200-nanosecond fully solvated molecular dynamics simulation. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[2]  Laxmikant V. Kale,et al.  NAMD2: Greater Scalability for Parallel Molecular Dynamics , 1999 .

[3]  Steve Plimpton,et al.  Fast parallel algorithms for short-range molecular dynamics , 1993 .

[4]  Joel H. Saltz,et al.  Parallelizing Molecular Dynamics Programs for Distributed Memory Machines: An Application of the Cha , 1994 .

[5]  Laxmikant V. Kalé,et al.  NAMD: a Parallel, Object-Oriented Molecular Dynamics Program , 1996, Int. J. High Perform. Comput. Appl..

[6]  Laxmikant V. Kalé,et al.  Multiparadigm, Multilingual Interoperability: Experience with Converse , 1998, IPPS/SPDP Workshops.

[7]  Steven J. Plimpton,et al.  A new parallel method for molecular dynamics simulation of macromolecular systems , 1994, J. Comput. Chem..

[8]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[9]  Peter A. Kollman,et al.  AMBER: Assisted model building with energy refinement. A general program for modeling molecules and their interactions , 1981 .

[10]  Steven J. Plimpton,et al.  Particle{Mesh Ewald and rRESPA for Parallel Molecular Dynamics Simulations , 1997 .

[11]  Laxmikant V. Kalé,et al.  NAMD: A Case Study in Multilingual Parallel Programming , 1997, LCPC.

[12]  John A. Board,et al.  Distributed P trticle-Mesh Ewald: A Parallel Ewald Summation Method , 1996, PDPTA.

[13]  R.K. Brunner,et al.  Adapting to load on workstation clusters , 1999, Proceedings. Frontiers '99. Seventh Symposium on the Frontiers of Massively Parallel Computation.

[14]  Laxmikant V. Kalé,et al.  CHARM++: a portable concurrent object oriented system based on C++ , 1993, OOPSLA '93.

[15]  John A. Board,et al.  A portable distributed implementation of the parallel multipole tree algorithm , 1995, Proceedings of the Fourth IEEE International Symposium on High Performance Distributed Computing.