Overcoming Instabilities in Verlet-I/r-RESPA with the Mollified Impulse Method

The primary objective of this paper is to explain the derivation of symplectic mollified Verlet-I/r-RESPA (MOLLY) methods that overcome linear and nonlinear instabilities that arise as numerical artifacts in Verlet-I/r-RESPA. These methods allow for lengthening of the longest time step used in molecular dynamics (MD). We provide evidence that MOLLY methods can take a longest time step that is 50% greater than that of Verlet-I/r-RESPA, for a given drift, including no drift. A 350% increase in the timestep is possible using MOLLY with mild Langevin damping while still computing dynamic properties accurately. Furthermore, longer time steps also enhance the scalability of multiple time stepping integrators that use the popular Particle Mesh Ewald method for computing full electrostatics, since the parallel bottleneck of the fast Fourier transform associated with PME is invoked less often. An additional objective of this paper is to give sufficient implementation details for these mollified integrators, so that interested users may implement them into their MD codes, or use the program ProtoMol in which we have implemented these methods.

[1]  L. R. Scott,et al.  Parallelizing molecular dynamics using spatial decomposition , 1994, Proceedings of IEEE Scalable High Performance Computing Conference.

[2]  Jeremy G. Siek,et al.  The Matrix Template Library: A Unifying Framework for Numerical Linear Algebra , 1998, ECOOP Workshops.

[3]  B. Berne,et al.  A Multiple-Time-Step Molecular Dynamics Algorithm for Macromolecules , 1994 .

[4]  J. M. Sanz-Serna,et al.  Numerical Hamiltonian Problems , 1994 .

[5]  Robert D. Skeel,et al.  Integration Schemes for Molecular Dynamics and Related Applications , 1999 .

[6]  Sebastian Reich,et al.  Dynamical Systems, Numerical Integration, and Exponentially Small Estimates , 1998 .

[7]  David Brown,et al.  A domain decomposition parallel processing algorithm for molecular dynamics simulations of systems of arbitrary connectivity. , 1997 .

[8]  David M. Beazley,et al.  Message-Passing Multi-Cell Molecular Dynamics on the Connection Machine 5 , 1994, Parallel Comput..

[9]  T. Darden,et al.  Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems , 1993 .

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

[11]  J. Andrew McCammon,et al.  OOMPAA-Object-Oriented Model for Probing Assemblages of Atoms , 1999 .

[12]  Desmond J. Higham,et al.  Numerical Analysis 1997 , 1997 .

[13]  Kenneth M. Merz,et al.  A highly portable parallel implementation of AMBER4 using the message passing interface standard , 1995, J. Comput. Chem..

[14]  Robert D. Skeel,et al.  Symplectic Integration with Variable Stepsize , 1994 .

[15]  W. L. Jorgensen,et al.  Comparison of simple potential functions for simulating liquid water , 1983 .

[16]  Andreas Griewank,et al.  Algorithm 755: ADOL-C: a package for the automatic differentiation of algorithms written in C/C++ , 1996, TOMS.

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

[18]  Thierry Matthey,et al.  ProtoMol: A Molecular Dynamics Framework with Incremental Parallelization , 2001, PPSC.

[19]  J. M. Haile,et al.  Molecular dynamics simulation : elementary methods / J.M. Haile , 1992 .

[20]  Jesús A. Izaguirre,et al.  The Five Femtosecond Time Step Barrier , 1999, Computational Molecular Dynamics.

[21]  Mark E. Tuckerman,et al.  Reversible multiple time scale molecular dynamics , 1992 .

[22]  K. Schulten,et al.  Difficulties with multiple time stepping and fast multipole algorithm in molecular dynamics , 1997 .

[23]  Robert D. Skeel,et al.  Dangers of multiple time step methods , 1993 .

[24]  Axel T. Brunger,et al.  X-PLOR Version 3.1: A System for X-ray Crystallography and NMR , 1992 .

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

[26]  Herman J. C. Berendsen,et al.  Molecular Dynamics Simulations: The Limits and Beyond , 1999, Computational Molecular Dynamics.

[27]  R. Skeel,et al.  Nonlinear Resonance Artifacts in Molecular Dynamics Simulations , 1998 .

[28]  Berend Smit,et al.  Understanding molecular simulation: from algorithms to applications , 1996 .

[29]  Todd L. Veldhuizen,et al.  Techniques for Scientific C , 1999 .

[30]  J. Izaguirre Longer Time Steps for Molecular Dynamics , 1999 .

[31]  Todd L. Veldhuizen Blitz++: The Library that Thinks it is a Compiler , 2000 .

[32]  T. Schlick,et al.  Overcoming stability limitations in biomolecular dynamics. I. Combining force splitting via extrapolation with Langevin dynamics in LN , 1998 .

[33]  Tamar Schlick,et al.  A Family of Symplectic Integrators: Stability, Accuracy, and Molecular Dynamics Applications , 1997, SIAM J. Sci. Comput..

[34]  T. Schlick,et al.  Masking Resonance Artifacts in Force-Splitting Methods for Biomolecular Simulations by Extrapolative Langevin Dynamics , 1999 .

[35]  Mark Ainsworth,et al.  The graduate student's guide to numerical analysis '98 : lecture notes from the VIII EPSRC Summer School in Numerical Analysis , 1999 .

[36]  T. Ohwada Higher Order Approximation Methods for the Boltzmann Equation , 1998 .

[37]  M. A. López-Marcos,et al.  Explicit Symplectic Integrators Using Hessian-Vector Products , 1997, SIAM J. Sci. Comput..

[38]  Robert D. Skeel,et al.  Macromolecular dynamics on a shared‐memory multiprocessor , 1991 .

[39]  Alexander D. MacKerell,et al.  All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.

[40]  Roger T. Hanlon,et al.  PROCEEDINGS OF AN INTERNATIONAL MEETING: RIBOSOMAL RNA PHYLOGENY OF SELECTED MAJOR CLADES IN THE MOLLUSCA , 1997 .

[41]  Lee R. Nackman,et al.  Scientific and Engineering C++: An Introduction with Advanc , 1995, IEEE Computational Science and Engineering.

[42]  Thierry Matthey,et al.  ProtoMol, an object-oriented framework for prototyping novel algorithms for molecular dynamics , 2004, TOMS.

[43]  David M. Beazley,et al.  Lightweight Computational Steering of Very Large Scale Molecular Dynamics Simulations , 1996, Proceedings of the 1996 ACM/IEEE Conference on Supercomputing.

[44]  A. Leach Molecular Modelling: Principles and Applications , 1996 .

[45]  R. Skeel,et al.  Langevin stabilization of molecular dynamics , 2001 .

[46]  Bjarne Stroustrup,et al.  C++ : programovací jazyk : The C++ programming language (Orig.) , 1997 .

[47]  Tamar Schlick,et al.  Some Failures and Successes of Long-Timestep Approaches to Biomolecular Simulations , 1999, Computational Molecular Dynamics.

[48]  Robert D. Skeel,et al.  Long-Time-Step Methods for Oscillatory Differential Equations , 1998, SIAM J. Sci. Comput..

[49]  M Karplus,et al.  Molecular dynamics: applications to proteins. , 1986, Annals of the New York Academy of Sciences.

[50]  Ralph Johnson,et al.  design patterns elements of reusable object oriented software , 2019 .

[51]  Mark E. Tuckerman,et al.  Exploiting multiple levels of parallelism in Molecular Dynamics based calculations via modern techniques and software paradigms on distributed memory computers , 2000 .

[52]  Thierry Matthey,et al.  Evaluation of MPI's One-Sided Communication Mechanism for Short-Range Molecular Dynamics on the Origin2000 , 2000, PARA.

[53]  James Crotinger,et al.  How templates enable high-performance scientific computing in C++ , 1999, Comput. Sci. Eng..

[54]  Klaus Schulten,et al.  Generalized Verlet Algorithm for Efficient Molecular Dynamics Simulations with Long-range Interactions , 1991 .

[55]  T. Schlick,et al.  Extrapolation versus impulse in multiple-timestepping schemes. II. Linear analysis and applications to Newtonian and Langevin dynamics , 1998 .

[56]  T. Schlick,et al.  Special stability advantages of position-Verlet over velocity-Verlet in multiple-time step integration , 2001 .