An Overview of a Grid Architecture for Scientific Computing

This document gives an overview of a Grid testbed architecture proposal for the NorduGrid project. The aim of the project is to establish an inter-Nordic testbed facility for implementation of wide area computing and data handling. The architecture is supposed to define a Grid system suitable for solving data intensive problems at the Large Hadron Collider at CERN. We present the various architecture components needed for such a system. After that we go on to give a description of the dynamics by showing the task flow

The AliEn system, status and perspectives

AliEn is a production environment that implements several components of the Grid paradigm needed to simulate, reconstruct and analyse HEP data in a distributed way. The system is built around Open Source components, uses the Web Services model and standard network protocols to implement the computing platform that is currently being used to produce and analyse Monte Carlo data at over 30 sites on four continents. The aim of this paper is to present the current AliEn architecture and outline its future developments in the light of emerging standards.Comment: Talk from the 2003 Computing in High Energy and Nuclear Physics (CHEP03), La Jolla, Ca, USA, March 2003, 10 pages, Word, 10 figures. PSN MOAT00

Two ways to Grid: the contribution of Open Grid Services Architecture (OGSA) mechanisms to service-centric and resource-centric lifecycles

Service Oriented Architectures (SOAs) support service lifecycle tasks, including Development, Deployment, Discovery and Use. We observe that there are two disparate ways to use Grid SOAs such as the Open Grid Services Architecture (OGSA) as exemplified in the Globus Toolkit (GT3/4). One is a traditional enterprise SOA use where end-user services are developed, deployed and resourced behind firewalls, for use by external consumers: a service-centric (or ‘first-order’) approach. The other supports end-user development, deployment, and resourcing of applications across organizations via the use of execution and resource management services: A Resource-centric (or ‘second-order’) approach. We analyze and compare the two approaches using a combination of empirical experiments and an architectural evaluation methodology (scenario, mechanism, and quality attributes) to reveal common and distinct strengths and weaknesses. The impact of potential improvements (which are likely to be manifested by GT4) is estimated, and opportunities for alternative architectures and technologies explored. We conclude by investigating if the two approaches can be converged or combined, and if they are compatible on shared resources

GRIDCC - Providing a real-time grid for distributed instrumentation

The GRIDCC project is extending the use of Grid computing to include access to and control of distributed instrumentation. Access to the instruments will be via an interface to a Virtual Instrument Grid Service (VIGS). VIGS is a new concept and its design and implementation, together with middleware that can provide the appropriate Quality of Service (QoS), is a key part of the GRIDCC development plan. An overall architecture for GRIDCC has been defined and some of the application areas, which include distributed power systems, remote control of an accelerator and the remote monitoring of a large particle physics experiment, are briefly discussed.E

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

Grid applications for the BaBar experiment

This paper discusses the use of e-Science Grid in providing computational resources for modern international High Energy Physics (HEP) experiments. We investigate the suitability of the current generation of Grid software to provide the necessary resources to perform large-scale simulation of the experiment and analysis of data in the context of multinational collaboration

Supporting simulation in industry through the application of grid computing

An increased need for collaborative research, together with continuing advances in communication technology and computer hardware, has facilitated the development of distributed systems that can provide users access to geographically dispersed computing resources that are administered in multiple computer domains. The term grid computing, or grids, is popularly used to refer to such distributed systems. Simulation is characterized by the need to run multiple sets of computationally intensive experiments. Large scale scientific simulations have traditionally been the primary benefactor of grid computing. The application of this technology to simulation in industry has, however, been negligible. This research investigates how grid technology can be effectively exploited by users to model simulations in industry. It introduces our desktop grid, WinGrid, and presents a case study conducted at a leading European investment bank. Results indicate that grid computing does indeed hold promise for simulation in industry