51,116 research outputs found
A service oriented architecture for engineering design
Decision making in engineering design can be effectively addressed by using genetic algorithms to solve multi-objective problems. These multi-objective genetic algorithms
(MOGAs) are well suited to implementation in a Service Oriented Architecture. Often the evaluation process of the MOGA is compute-intensive due to the use of a complex computer model to represent the real-world system. The emerging paradigm of Grid Computing offers
a potential solution to the compute-intensive nature of this objective function evaluation, by
allowing access to large amounts of compute resources in a distributed manner. This paper presents a grid-enabled framework for multi-objective optimisation using genetic algorithms (MOGA-G) to aid decision making in engineering design
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
Jeeva: Enterprise Grid-enabled Web Portal for Protein Secondary Structure Prediction
This paper presents a Grid portal for protein secondary structure prediction
developed by using services of Aneka, a .NET-based enterprise Grid technology.
The portal is used by research scientists to discover new prediction structures
in a parallel manner. An SVM (Support Vector Machine)-based prediction
algorithm is used with 64 sample protein sequences as a case study to
demonstrate the potential of enterprise Grids.Comment: 7 page
A grid-enabled problem solving environment for parallel computational engineering design
This paper describes the development and application of a piece of engineering software that provides a problem solving environment (PSE) capable of launching, and interfacing with, computational jobs executing on remote resources on a computational grid. In particular it is demonstrated how a complex, serial, engineering optimisation code may be efficiently parallelised, grid-enabled and embedded within a PSE.
The environment is highly flexible, allowing remote users from different sites to collaborate, and permitting computational tasks to be executed in parallel across multiple grid resources, each of which may be a parallel architecture. A full working prototype has been built and successfully applied to a computationally demanding engineering optimisation problem. This particular problem stems from elastohydrodynamic lubrication and involves optimising the computational model for a lubricant based on the match between simulation results and experimentally observed data
Distributed N-body Simulation on the Grid Using Dedicated Hardware
We present performance measurements of direct gravitational N -body
simulation on the grid, with and without specialized (GRAPE-6) hardware. Our
inter-continental virtual organization consists of three sites, one in Tokyo,
one in Philadelphia and one in Amsterdam. We run simulations with up to 196608
particles for a variety of topologies. In many cases, high performance
simulations over the entire planet are dominated by network bandwidth rather
than latency. With this global grid of GRAPEs our calculation time remains
dominated by communication over the entire range of N, which was limited due to
the use of three sites. Increasing the number of particles will result in a
more efficient execution. Based on these timings we construct and calibrate a
model to predict the performance of our simulation on any grid infrastructure
with or without GRAPE. We apply this model to predict the simulation
performance on the Netherlands DAS-3 wide area computer. Equipping the DAS-3
with GRAPE-6Af hardware would achieve break-even between calculation and
communication at a few million particles, resulting in a compute time of just
over ten hours for 1 N -body time unit. Key words: high-performance computing,
grid, N-body simulation, performance modellingComment: (in press) New Astronomy, 24 pages, 5 figure
gcodeml: A Grid-enabled Tool for Detecting Positive Selection in Biological Evolution
One of the important questions in biological evolution is to know if certain
changes along protein coding genes have contributed to the adaptation of
species. This problem is known to be biologically complex and computationally
very expensive. It, therefore, requires efficient Grid or cluster solutions to
overcome the computational challenge. We have developed a Grid-enabled tool
(gcodeml) that relies on the PAML (codeml) package to help analyse large
phylogenetic datasets on both Grids and computational clusters. Although we
report on results for gcodeml, our approach is applicable and customisable to
related problems in biology or other scientific domains.Comment: 10 pages, 4 figures. To appear in the HealthGrid 2012 con
Large-scale grid-enabled lattice-Boltzmann simulations of complex fluid flow in porous media and under shear
Well designed lattice-Boltzmann codes exploit the essentially embarrassingly
parallel features of the algorithm and so can be run with considerable
efficiency on modern supercomputers. Such scalable codes permit us to simulate
the behaviour of increasingly large quantities of complex condensed matter
systems. In the present paper, we present some preliminary results on the large
scale three-dimensional lattice-Boltzmann simulation of binary immiscible fluid
flows through a porous medium derived from digitised x-ray microtomographic
data of Bentheimer sandstone, and from the study of the same fluids under
shear. Simulations on such scales can benefit considerably from the use of
computational steering and we describe our implementation of steering within
the lattice-Boltzmann code, called LB3D, making use of the RealityGrid steering
library. Our large scale simulations benefit from the new concept of capability
computing, designed to prioritise the execution of big jobs on major
supercomputing resources. The advent of persistent computational grids promises
to provide an optimal environment in which to deploy these mesoscale simulation
methods, which can exploit the distributed nature of compute, visualisation and
storage resources to reach scientific results rapidly; we discuss our work on
the grid-enablement of lattice-Boltzmann methods in this context.Comment: 17 pages, 6 figures, accepted for publication in
Phil.Trans.R.Soc.Lond.
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