275 research outputs found
Efficient Molecular Dynamics Simulation on Reconfigurable 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
Particle-Particle, Particle-Scaling function (P3S) algorithm for electrostatic problems in free boundary conditions
An algorithm for fast calculation of the Coulombic forces and energies of
point particles with free boundary conditions is proposed. Its calculation time
scales as N log N for N particles. This novel method has lower crossover point
with the full O(N^2) direct summation than the Fast Multipole Method. The
forces obtained by our algorithm are analytical derivatives of the energy which
guarantees energy conservation during a molecular dynamics simulation. Our
algorithm is very simple. An MPI parallelised version of the code can be
downloaded under the GNU General Public License from the website of our group.Comment: 19 pages, 11 figures, submitted to: Journal of Chemical Physic
A Continuum,O(N) Monte-Carlo algorithm for charged particles
We introduce a Monte-Carlo algorithm for the simulation of charged particles
moving in the continuum. Electrostatic interactions are not instantaneous as in
conventional approaches, but are mediated by a constrained, diffusing electric
field on an interpolating lattice. We discuss the theoretical justifications of
the algorithm and show that it efficiently equilibrates model polyelectrolytes
and polar fluids. In order to reduce lattice artifacts that arise from the
interpolation of charges to the grid we implement a local, dynamic subtraction
algorithm. This dynamic scheme is completely general and can also be used with
other Coulomb codes, such as multigrid based methods
Improvements to the APBS biomolecular solvation software suite
The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve
the equations of continuum electrostatics for large biomolecular assemblages
that has provided impact in the study of a broad range of chemical, biological,
and biomedical applications. APBS addresses three key technology challenges for
understanding solvation and electrostatics in biomedical applications: accurate
and efficient models for biomolecular solvation and electrostatics, robust and
scalable software for applying those theories to biomolecular systems, and
mechanisms for sharing and analyzing biomolecular electrostatics data in the
scientific community. To address new research applications and advancing
computational capabilities, we have continually updated APBS and its suite of
accompanying software since its release in 2001. In this manuscript, we discuss
the models and capabilities that have recently been implemented within the APBS
software package including: a Poisson-Boltzmann analytical and a
semi-analytical solver, an optimized boundary element solver, a geometry-based
geometric flow solvation model, a graph theory based algorithm for determining
p values, and an improved web-based visualization tool for viewing
electrostatics
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