Parallel memetic algorithms for independent job scheduling in computational grids

In this chapter we present parallel implementations of Memetic Algorithms (MAs) for the problem of scheduling independent jobs in computational grids. The problem of scheduling in computational grids is known for its high demanding computational time. In this work we exploit the intrinsic parallel nature of MAs as well as the fact that computational grids offer large amount of resources, a part of which could be used to compute the efficient allocation of jobs to grid resources. The parallel models exploited in this work for MAs include both fine-grained and coarse-grained parallelization and their hybridization. The resulting schedulers have been tested through different grid scenarios generated by a grid simulator to match different possible configurations of computational grids in terms of size (number of jobs and resources) and computational characteristics of resources. All in all, the result of this work showed that Parallel MAs are very good alternatives in order to match different performance requirement on fast scheduling of jobs to grid resources.Peer ReviewedPostprint (author's final draft

Adaptive Wavelet Collocation Method for Simulation of Time Dependent Maxwell's Equations

This paper investigates an adaptive wavelet collocation time domain method for the numerical solution of Maxwell's equations. In this method a computational grid is dynamically adapted at each time step by using the wavelet decomposition of the field at that time instant. In the regions where the fields are highly localized, the method assigns more grid points; and in the regions where the fields are sparse, there will be less grid points. On the adapted grid, update schemes with high spatial order and explicit time stepping are formulated. The method has high compression rate, which substantially reduces the computational cost allowing efficient use of computational resources. This adaptive wavelet collocation method is especially suitable for simulation of guided-wave optical devices

Automatic grid refinement criterion for lattice Boltzmann method

In all kinds of engineering problems, and in particular in methods for computational fluid dynamics based on regular grids, local grid refinement is of crucial importance. To save on computational expense, many applications require to resolve a wide range of scales present in a numerical simulation by locally adding more mesh points. In general, the need for a higher (or a lower) resolution is not known a priori, and it is therefore difficult to locate areas for which local grid refinement is required. In this paper, we propose a novel algorithm for the lattice Boltzmann method, based on physical concepts, to automatically construct a pattern of local refinement. We apply the idea to the two-dimensional lid-driven cavity and show that the automatically refined grid can lead to results of equal quality with less grid points, thus sparing computational resources and time. The proposed automatic grid refinement strategy has been implemented in the parallel open-source library Palabos

Developing web services in a computational grid environment

Grid and Web services are both hot topics today. In this paper, we will present some ongoing work and planned future work at the Cambridge eScience Centre. After an introduction to these technologies in the context of Grid applications development, we describe two use-cases: a database of results in computational fluid dynamics (CFD) and a small computational Grid for aircraft engineering design. As Grid services are moving towards Web services, we continue to make use of the Globus Toolkit v2.4 (GT2.4), without adopting the Open Grid Services Architecture (OGSA) wholesale. In our scenario, GT2.4 integrates distributed computing resources including HPC and clusters while Web services wrap the scientific code as a service.Proceedings of the IEEE International Conference on Services Computing, Shanghai, September 200

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

Computational modes and grid imprinting on five quasi-uniform spherical C-grids

Currently, most operational forecasting models use latitude-longitude grids, whose convergence of meridians towards the poles limits parallel scaling. Quasi-uniform grids might avoid this limitation. Thuburn et al, JCP, 2009 and Ringler et al, JCP, 2010 have developed a method for arbitrarily-structured, orthogonal C-grids (TRiSK), which has many of the desirable properties of the C-grid on latitude-longitude grids but which works on a variety of quasi-uniform grids. Here, five quasi-uniform, orthogonal grids of the sphere are investigated using TRiSK to solve the shallow-water equations. We demonstrate some of the advantages and disadvantages of the hexagonal and triangular icosahedra, a Voronoi-ised cubed sphere, a Voronoi-ised skipped latitude-longitude grid and a grid of kites in comparison to a full latitude-longitude grid. We will show that the hexagonal-icosahedron gives the most accurate results (for least computational cost). All of the grids suffer from spurious computational modes; this is especially true of the kite grid, despite it having exactly twice as many velocity degrees of freedom as height degrees of freedom. However, the computational modes are easiest to control on the hexagonal icosahedron since they consist of vorticity oscillations on the dual grid which can be controlled using a diffusive advection scheme for potential vorticity

M-grid: Using Ubiquitous Web Technologies to create a Computational Grid

There are many potential users and uses for grid computing. However, the concept of sharing computing resources excites security concerns and, whilst being powerful and flexible, at least for novices, existing systems are complex to install and use. Together these represent a significant barrier to potential users who are interested to see what grid computing can do. This paper describes m-grid, a system for building a computational grid which can accept tasks from any user with access to a web browser and distribute them to almost any machine with access to the internet and manages to do this without the installation of additional software or interfering with existing security arrangements

Managing Uncertainty: A Case for Probabilistic Grid Scheduling

The Grid technology is evolving into a global, service-orientated architecture, a universal platform for delivering future high demand computational services. Strong adoption of the Grid and the utility computing concept is leading to an increasing number of Grid installations running a wide range of applications of different size and complexity. In this paper we address the problem of elivering deadline/economy based scheduling in a heterogeneous application environment using statistical properties of job historical executions and its associated meta-data. This approach is motivated by a study of six-month computational load generated by Grid applications in a multi-purpose Grid cluster serving a community of twenty e-Science projects. The observed job statistics, resource utilisation and user behaviour is discussed in the context of management approaches and models most suitable for supporting a probabilistic and autonomous scheduling architecture