Effic ient Molecular Dynamics Simulation on Reconfi gurable Models with MultiGrid Method

In the field of biology, MD simulations are continuously used to investigate biological studies. A Molecular Dynamics (MD) system is defined by the position and momentum of particles and their interactions. The dynamics of a system can be evaluated by an N-body problem and the simulation is continued until the energy reaches equilibrium. Thus, solving the dynamics numerically and evaluating the interaction is computationally expensive even for a small number of particles in the system. We are focusing on long-ranged interactions, since the calculation time is O(N 2 ) for an N particle system. In this dissertation, we are proposing two research directions for the MD simulation. First, we design a new variation of Multigrid (MG) algorithm called Multi-level charge assignment (MCA) that requires O(N) time for accurate and efficient calculation of the electrostatic forces. We apply MCA and back interpolation based on the structure of molecules to enhance the accuracy of the simulation. Our second research utilizes reconfigurable models to achieve fast calculation time. We have been working on exploiting two reconfigurable models. We design FPGA-based MD simulator implementing MCA method for Xilinx Virtex-IV. It performs about 10 to 100 times faster than software implementation depending on the simulation accuracy desired. We also design fast and scalable Reconfigurable mesh (R-Mesh) algorithms for MD simulations. This work demonstrates that the large scale biological studies can be simulated in close to real time. The R-Mesh algorithms we design highlight the feasibility of these models to evaluate potentials with faster calculation times. Specifically, we develop R-Mesh algorithms for both Direct method and Multigrid method. The Direct method evaluates exact potentials and forces, but requires O(N 2 ) calculation time for evaluating electrostatic forces on a general purpose processor. The MG method adopts an interpolation technique to reduce calculation time to O(N) for a given accuracy. However, our R-Mesh algorithms require only O(N) or O(logN) time complexity for the Direct method on N linear R-Mesh and N×N R-Mesh, respectively and O(r)+O(logM) time complexity for the Multigrid method on an X×Y×Z R-Mesh. r is N/M and M = X×Y×Z is the number of finest grid points. INDEX WORDS : Molecular Dynamics Simulation, Multigrid, Reconfigurable Model, Reconfigurable Mesh Algorithm, FPGA EFFICIENT MOLECULAR DYNAMICS SIMULATION ON RECONFIGURABLE MODELS WITH MULTIGRID METHOD

[1]  Robert S. Germain,et al.  Blue Matter, an application framework for molecular simulation on Blue Gene , 2003, J. Parallel Distributed Comput..

[2]  Dionysios I. Reisis,et al.  Parallel Computations on Reconfigurable Meshes , 1993, IEEE Trans. Computers.

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

[4]  Sartaj Sahni,et al.  Reconfigurable mesh algorithms for image shrinking, expanding, clustering, and template matching , 1991, [1991] Proceedings. The Fifth International Parallel Processing Symposium.

[5]  S. W. Leeuw,et al.  An Iterative PPPM Method for Simulating Coulombic Systems on Distributed Memory Parallel Computers , 1998 .

[6]  Eunjung Cho,et al.  An FPGA Design to Achieve Fast and Accurate Results for Molecular Dynamics Simulations , 2007, ISPA.

[7]  Ramachandran Vaidyanathan,et al.  Dynamic reconfiguration - architectures and algorithms , 2003, Series in computer science.

[8]  Jerry L. Trahan,et al.  Fault tolerant algorithms for a linear array with a reconfigurable pipelined bus system* , 2003, Parallel Algorithms Appl..

[9]  Efficient Molecular Dynamics ( MD ) simulation on Field Programmable Gate Array ( FPGA ) s with MultiGrid method , 2007 .

[10]  Darrin M. York,et al.  The fast Fourier Poisson method for calculating Ewald sums , 1994 .

[11]  Makoto Taiji,et al.  Fast and accurate molecular dynamics simulation of a protein using a special-purpose computer , 1997, J. Comput. Chem..

[12]  C. Sagui,et al.  Multigrid methods for classical molecular dynamics simulations of biomolecules , 2001 .

[13]  Jean-Marc Jézéquel,et al.  Implementing and evaluating an efficient dynamic load-balancer for distributed molecular dynamics simulation , 2000, Proceedings 2000. International Workshop on Parallel Processing.

[14]  Nobuaki Miyakawa,et al.  Development of MD Engine: High-speed accelerator with parallel processor design for molecular dynamics simulations , 1999, J. Comput. Chem..

[15]  Russ Miller,et al.  Meshes with reconfigurable buses , 1988 .

[16]  C. Brooks Computer simulation of liquids , 1989 .

[17]  Robert D. Skeel,et al.  Multiple grid methods for classical molecular dynamics , 2002, J. Comput. Chem..

[18]  Quentin F. Stout,et al.  Reconfigurable SIMD massively parallel computers , 1991 .

[19]  Jerry L. Trahan,et al.  Tighter and Broader Complexity Results for Reconfigurable Models , 1998, Parallel Process. Lett..

[20]  T. Darden,et al.  Molecular dynamics simulations of biomolecules: long-range electrostatic effects. , 1999, Annual review of biophysics and biomolecular structure.

[21]  Koji Nakano,et al.  A Bibliography of Published Papers on Dynamically Reconfigurable Architectures , 1995, Parallel Process. Lett..

[22]  Thierry Matthey,et al.  Parallel multigrid summation for the N-body problem , 2005, J. Parallel Distributed Comput..

[23]  Jerry L. Trahan,et al.  Scaling Simulation of the Fusing-Restricted Reconfigurable Mesh , 1998, IEEE Trans. Parallel Distributed Syst..

[24]  Sadaf R. Alam,et al.  On the Path to Enable Multi-scale Biomolecular Simulations on PetaFLOPS Supercomputer with Multi-core Processors , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[25]  Sadaf R. Alam,et al.  Biomolecular simulations on petascale: promises and challenges , 2006 .

[26]  J. Board,et al.  Ewald summation techniques in perspective: a survey , 1996 .

[27]  Martin C. Herbordt,et al.  Accelerating molecular dynamics simulations with configurable circuits , 2005, International Conference on Field Programmable Logic and Applications, 2005..

[28]  TAKASHI AMISAKI,et al.  Error evaluation in the design of a special‐purpose processor that calculates nonbonded forces in molecular dynamics simulations , 1995, J. Comput. Chem..

[29]  Jerry L. Trahan,et al.  Relating two-dimensional reconfigurable meshes with optically pipelined buses , 2000, Proceedings 14th International Parallel and Distributed Processing Symposium. IPDPS 2000.

[30]  Gregory Ray Goslin,et al.  Guide to using field programmable gate arrays (FPGAs) for application-specific digital signal processing performance , 1996, Other Conferences.

[31]  M.G.B. Drew,et al.  The art of molecular dynamics simulation , 1996 .

[32]  T Fukushige,et al.  A high performance system for molecular dynamics simulation of biomolecules using a special-purpose computer. , 1996, Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing.

[33]  Andreas Gebhardt,et al.  Rapid prototyping , 2003 .

[34]  Eunjung Cho,et al.  Efficient and accurate FPGA-based simulator for Molecular Dynamics , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[35]  Aravind Dasu,et al.  A Reconfigurable Load Balancing Architecture for Molecular Dynamics , 2007, 2007 IEEE International Parallel and Distributed Processing Symposium.

[36]  Thomas A. Darden,et al.  Adventures in Improving the Scaling and Accuracy of a Parallel Molecular Dynamics Program , 1997, The Journal of Supercomputing.

[37]  David Peleg,et al.  The Power of Reconfiguration , 1991, J. Parallel Distributed Comput..

[38]  Paul Chow,et al.  Reconfigurable molecular dynamics simulator , 2004, 12th Annual IEEE Symposium on Field-Programmable Custom Computing Machines.

[39]  Eunjung Cho,et al.  Examining the Feasibility of Reconfigurable Models for Molecular Dynamics Simulation , 2008, ICA3PP.

[40]  Sadaf R. Alam,et al.  Performance characterization of molecular dynamics techniques for biomolecular simulations , 2006, PPoPP '06.

[41]  Sullivan,et al.  Real-space multigrid-based approach to large-scale electronic structure calculations. , 1996, Physical review. B, Condensed matter.

[42]  Jerry L. Trahan,et al.  Fault Tolerant Algorithms for a Linear Array with a Reconfigurable Pipelined Bus System , 2000, IPDPS Workshops.