22,576 research outputs found
Open-architecture Implementation of Fragment Molecular Orbital Method for Peta-scale Computing
We present our perspective and goals on highperformance computing for
nanoscience in accordance with the global trend toward "peta-scale computing."
After reviewing our results obtained through the grid-enabled version of the
fragment molecular orbital method (FMO) on the grid testbed by the Japanese
Grid Project, National Research Grid Initiative (NAREGI), we show that FMO is
one of the best candidates for peta-scale applications by predicting its
effective performance in peta-scale computers. Finally, we introduce our new
project constructing a peta-scale application in an open-architecture
implementation of FMO in order to realize both goals of highperformance in
peta-scale computers and extendibility to multiphysics simulations.Comment: 6 pages, 9 figures, proceedings of the 2nd IEEE/ACM international
workshop on high performance computing for nano-science and technology
(HPCNano06
Grid service orchestration using the Business Process Execution Language (BPEL)
Modern scientific applications often need to be distributed across grids. Increasingly
applications rely on services, such as job submission, data transfer or data
portal services. We refer to such services as grid services. While the invocation
of grid services could be hard coded in theory, scientific users want to orchestrate
service invocations more flexibly. In enterprise applications, the orchestration of
web services is achieved using emerging orchestration standards, most notably
the Business Process Execution Language (BPEL). We describe our experience
in orchestrating scientific workflows using BPEL. We have gained this experience
during an extensive case study that orchestrates grid services for the automation of
a polymorph prediction application
Multi-Architecture Monte-Carlo (MC) Simulation of Soft Coarse-Grained Polymeric Materials: SOft coarse grained Monte-carlo Acceleration (SOMA)
Multi-component polymer systems are important for the development of new
materials because of their ability to phase-separate or self-assemble into
nano-structures. The Single-Chain-in-Mean-Field (SCMF) algorithm in conjunction
with a soft, coarse-grained polymer model is an established technique to
investigate these soft-matter systems. Here we present an im- plementation of
this method: SOft coarse grained Monte-carlo Accelera- tion (SOMA). It is
suitable to simulate large system sizes with up to billions of particles, yet
versatile enough to study properties of different kinds of molecular
architectures and interactions. We achieve efficiency of the simulations
commissioning accelerators like GPUs on both workstations as well as
supercomputers. The implementa- tion remains flexible and maintainable because
of the implementation of the scientific programming language enhanced by
OpenACC pragmas for the accelerators. We present implementation details and
features of the program package, investigate the scalability of our
implementation SOMA, and discuss two applications, which cover system sizes
that are difficult to reach with other, common particle-based simulation
methods
Steering in computational science: mesoscale modelling and simulation
This paper outlines the benefits of computational steering for high
performance computing applications. Lattice-Boltzmann mesoscale fluid
simulations of binary and ternary amphiphilic fluids in two and three
dimensions are used to illustrate the substantial improvements which
computational steering offers in terms of resource efficiency and time to
discover new physics. We discuss details of our current steering
implementations and describe their future outlook with the advent of
computational grids.Comment: 40 pages, 11 figures. Accepted for publication in Contemporary
Physic
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
Fragment Approach to Constrained Density Functional Theory Calculations using Daubechies Wavelets
In a recent paper we presented a linear scaling Kohn-Sham density functional
theory (DFT) code based on Daubechies wavelets, where a minimal set of
localized support functions is optimized in situ and therefore adapted to the
chemical properties of the molecular system. Thanks to the systematically
controllable accuracy of the underlying basis set, this approach is able to
provide an optimal contracted basis for a given system: accuracies for ground
state energies and atomic forces are of the same quality as an uncontracted,
cubic scaling approach. This basis set offers, by construction, a natural
subset where the density matrix of the system can be projected. In this paper
we demonstrate the flexibility of this minimal basis formalism in providing a
basis set that can be reused as-is, i.e. without reoptimization, for
charge-constrained DFT calculations within a fragment approach. Support
functions, represented in the underlying wavelet grid, of the template
fragments are roto-translated with high numerical precision to the required
positions and used as projectors for the charge weight function. We demonstrate
the interest of this approach to express highly precise and efficient
calculations for preparing diabatic states and for the computational setup of
systems in complex environments
Calculation of absolute free energy of binding for theophylline and its analogs to RNA aptamer using nonequilibrium work values
The massively parallel computation of absolute binding free energy with a
well-equilibrated system (MP-CAFEE) has been developed [H. Fujitani, Y. Tanida,
M. Ito, G. Jayachandran, C. D. Snow, M. R. Shirts, E. J. Sorin, and V. S.
Pande, J. Chem. Phys. , 084108 (2005)]. As an application, we
perform the binding affinity calculations of six theophylline-related ligands
with RNA aptamer. Basically, our method is applicable when using many compute
nodes to accelerate simulations, thus a parallel computing system is also
developed. To further reduce the computational cost, the adequate non-uniform
intervals of coupling constant , connecting two equilibrium states,
namely bound and unbound, are determined. The absolute binding energies thus obtained have effective linear relation between the computed and
experimental values. If the results of two other different methods are
compared, thermodynamic integration (TI) and molecular mechanics
Poisson-Boltzmann surface area (MM-PBSA) by the paper of Gouda [H.
Gouda, I. D. Kuntz, D. A. Case, and P. A. Kollman, Biopolymers , 16
(2003)], the predictive accuracy of the relative values is
almost comparable to that of TI: the correlation coefficients (R) obtained are
0.99 (this work), 0.97 (TI), and 0.78 (MM-PBSA). On absolute binding energies
meanwhile, a constant energy shift of -7 kcal/mol against the
experimental values is evident. To solve this problem, several presumable
reasons are investigated.Comment: 23 pages including 6 figure
MGOS: A library for molecular geometry and its operating system
The geometry of atomic arrangement underpins the structural understanding of molecules in many fields. However, no general framework of mathematical/computational theory for the geometry of atomic arrangement exists. Here we present "Molecular Geometry (MG)'' as a theoretical framework accompanied by "MG Operating System (MGOS)'' which consists of callable functions implementing the MG theory. MG allows researchers to model complicated molecular structure problems in terms of elementary yet standard notions of volume, area, etc. and MGOS frees them from the hard and tedious task of developing/implementing geometric algorithms so that they can focus more on their primary research issues. MG facilitates simpler modeling of molecular structure problems; MGOS functions can be conveniently embedded in application programs for the efficient and accurate solution of geometric queries involving atomic arrangements. The use of MGOS in problems involving spherical entities is akin to the use of math libraries in general purpose programming languages in science and engineering. (C) 2019 The Author(s). Published by Elsevier B.V
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