Using a desktop grid to support simulation modelling

Simulation is characterized by the need to run multiple sets of computationally intensive experiments. We argue that Grid computing can reduce the overall execution time of such experiments by tapping into the typically underutilized network of departmental desktop PCs, collectively known as desktop grids. Commercial-off-the-shelf simulation packages (CSPs) are used in industry to simulate models. To investigate if Grid computing can benefit simulation, this paper introduces our desktop grid, WinGrid, and discusses how this can be used to support the processing needs of CSPs. Results indicate a linear speed up and that Grid computing does indeed hold promise for simulation

Speeding-up the execution of credit risk simulations using desktop grid computing: A case study

This paper describes a case study that was undertaken at a leading European Investment bank in which desktop grid computing was used to speed-up the execution of Monte Carlo credit risk simulations. The credit risk simulations were modelled using commercial-off-the-shelf simulation packages (CSPs). The CSPs did not incorporate built-in support for desktop grids, and therefore the authors implemented a middleware for desktop grid computing, called WinGrid, and interfaced it with the CSP. The performance results show that WinGrid can speed-up the execution of CSP-based Monte Carlo simulations. However, since WinGrid was installed on non-dedicated PCs, the speed-up achieved varied according to users’ PC usage. Finally, the paper presents some lessons learnt from this case study. It is expected that this paper will encourage simulation practitioners and CSP vendors to experiment with desktop grid computing technologies with the objective of speeding-up simulation experimentation

Leveraging simulation practice in industry through use of desktop grid middleware

This chapter focuses on the collaborative use of computing resources to support decision making in industry. Through the use of middleware for desktop grid computing, the idle CPU cycles available on existing computing resources can be harvested and used for speeding-up the execution of applications that have “non-trivial” processing requirements. This chapter focuses on the desktop grid middleware BOINC and Condor, and discusses the integration of commercial simulation software together with free-to-download grid middleware so as to offer competitive advantage to organizations that opt for this technology. It is expected that the low-intervention integration approach presented in this chapter (meaning no changes to source code required) will appeal to both simulation practitioners (as simulations can be executed faster, which in turn would mean that more replications and optimization is possible in the same amount of time) and the management (as it can potentially increase the return on investment on existing resources)

Dependency Modelling for Cultural Heritage

May 31st - June 3rd, 200

Integrating BOINC with Microsoft Excel: A case study

The convergence of conventional Grid computing with public resource computing (PRC) offers potential benefits in the enterprise setting. For this work we took the popular PRC toolkit BOINC and used it to execute a previously monolithic Microsoft Excel financial model across several commodity computers. Our experience indicates that speedup approaching linear may be realised for certain scenarios, and that this approach offers a viable route to leveraging idle desktop PCs in the enterprise

Nonlinear Cosmological Power Spectra in Real and Redshift--Space

We present an expression for the nonlinear evolution of the cosmological power spectrum based on following Lagrangian trajectories. This is simplified using the Zel'dovich approximation to trace particle displacements, assuming Gaussian initial conditions. The model is found to exhibit the transfer of power from large to small scales expected in self- gravitating fields. We have extended this analysis into redshift-space and found a solution for the nonlinear, anisotropic redshift-space power spectrum in the limit of plane--parallel redshift distortions. The quadrupole-to- monopole ratio is calculated for the case of power-law initial spectra. We find that the shape of this ratio depends on the shape of the initial spectrum, but when scaled to linear theory depends only weakly on the redshift-space distortion parameter, $\beta$. The point of zero-crossing of the quadrupole, $k_0$, is found to obey a scaling relation. This model is found to be in agreement with $N$-body simulations on scales down to the zero-crossing of the quadrupole, although the wavenumber at zero-crossing is underestimated. These results are applied to the quadrupole--monopole ratio found in the merged QDOT+1.2 Jy IRAS redshift survey. We have estimated that the distortion parameter is constrained to be $\beta>0.5$ at the $95 \%$ level. The local primordial spectral slope is not well constrained, but analysis suggests $n \approx -2$ in the translinear regime. The zero-crossing scale of the quadrupole is $k_0=0.5 \pm 0.1 h/Mpc$ and from this we infer the amplitude of clustering is $\sigma_8=0.7 \pm 0.05$. We suggest that the success of this model is due to nonlinear redshift--space effects arising from infall onto caustics and is not dominated by virialised cluster cores.Comment: 13 pages, uufiles, Latex with 6 postscript figures, submitted to MNRA

Mapping Cluster Mass Distributions via Gravitational Lensing of Background Galaxies

We present a new method for measuring the projected mass distributions of galaxy clusters. The gravitational amplification is measured by comparing the joint distribution in redshift and magnitude of galaxies behind the cluster with that of field galaxies. We show that the total amplification is directly related to the surface mass density in the weak field limit, and so it is possible to map the mass distribution of the cluster. The method is shown to be limited by discreteness noise and galaxy clustering behind the lens. Galaxy clustering sets a lower limit to the error along the redshift direction, but a clustering independent lensing signature may be obtained from the magnitude distribution at fixed redshift. Statistical techniques are developed for estimating the surface mass density of the cluster. We extend these methods to account for any obscuration by cluster halo dust, which may be mapped independently of the dark matter. We apply the method to a series of numerical simulations and show the feasibility of the approach. We consider approximate redshift information, and show how the mass estimates are degraded.Comment: ApJ in press. 23 pages of LaTeX plus figs. Text & figs available by anonymous ftp from resun03.roe.ac.uk in directory /pub/jap/lens (you need btp.tex and apj.sty

Methodology for profiling literature in healthcare simulation

The publications that relate to the application of simulation to healthcare have steadily increased over the years. These publications are scattered amongst various journals that belong to several subject categories, including Operational Research, Health Economics and Pharmacokinetics. The simulation techniques that are applied to the study of healthcare problems are also varied. The aim of this study is to present a methodology for profiling literature in healthcare simulation. In our methodology, we have considered papers on healthcare that have been published between 1970 and 2007 in journals with impact factors that belonging to various subject categories reporting on the application of four simulation techniques, namely, Monte Carlo Simulation, Discrete-Event Simulation, System Dynamics and Agent-Based Simulation. The methodology has the following objectives: (a) to categorise the papers under the different simulation techniques and identify the healthcare problems that each technique is employed to investigate; (b) to profile, within our dataset, variables such as authors, article citations, etc.; (c) to identify turning point (strategically important) papers and authors through co-citation analysis of references cited by the papers in our dataset. The focus of the paper is on the literature profiling methodology, and not the results that have been derived through the application of this methodology. The authors hope that the methodology presented here will be used to conduct similar work in not only healthcare but also other research domains