175,230 research outputs found
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
Pushing towards the Limit of Sampling Rate: Adaptive Chasing Sampling
Measurement samples are often taken in various monitoring applications. To
reduce the sensing cost, it is desirable to achieve better sensing quality
while using fewer samples. Compressive Sensing (CS) technique finds its role
when the signal to be sampled meets certain sparsity requirements. In this
paper we investigate the possibility and basic techniques that could further
reduce the number of samples involved in conventional CS theory by exploiting
learning-based non-uniform adaptive sampling.
Based on a typical signal sensing application, we illustrate and evaluate the
performance of two of our algorithms, Individual Chasing and Centroid Chasing,
for signals of different distribution features. Our proposed learning-based
adaptive sampling schemes complement existing efforts in CS fields and do not
depend on any specific signal reconstruction technique. Compared to
conventional sparse sampling methods, the simulation results demonstrate that
our algorithms allow less number of samples for accurate signal
reconstruction and achieve up to smaller signal reconstruction error
under the same noise condition.Comment: 9 pages, IEEE MASS 201
AstroGrid-D: Grid Technology for Astronomical Science
We present status and results of AstroGrid-D, a joint effort of
astrophysicists and computer scientists to employ grid technology for
scientific applications. AstroGrid-D provides access to a network of
distributed machines with a set of commands as well as software interfaces. It
allows simple use of computer and storage facilities and to schedule or monitor
compute tasks and data management. It is based on the Globus Toolkit middleware
(GT4). Chapter 1 describes the context which led to the demand for advanced
software solutions in Astrophysics, and we state the goals of the project. We
then present characteristic astrophysical applications that have been
implemented on AstroGrid-D in chapter 2. We describe simulations of different
complexity, compute-intensive calculations running on multiple sites, and
advanced applications for specific scientific purposes, such as a connection to
robotic telescopes. We can show from these examples how grid execution improves
e.g. the scientific workflow. Chapter 3 explains the software tools and
services that we adapted or newly developed. Section 3.1 is focused on the
administrative aspects of the infrastructure, to manage users and monitor
activity. Section 3.2 characterises the central components of our architecture:
The AstroGrid-D information service to collect and store metadata, a file
management system, the data management system, and a job manager for automatic
submission of compute tasks. We summarise the successfully established
infrastructure in chapter 4, concluding with our future plans to establish
AstroGrid-D as a platform of modern e-Astronomy.Comment: 14 pages, 12 figures Subjects: data analysis, image processing,
robotic telescopes, simulations, grid. Accepted for publication in New
Astronom
Mathematical Modelling of Chemical Diffusion through Skin using Grid-based PSEs
A Problem Solving Environment (PSE) with connections to remote distributed Grid processes is developed. The Grid simulation is itself a parallel process and allows steering of individual or multiple runs of the core computation of chemical diffusion through the stratum corneum, the outer layer of the skin. The effectiveness of this Grid-based approach in improving the quality of the simulation is assessed
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