Grid computing

Summary

Grid computing is the use of widely distributed computer resources to reach a common goal. A computing grid can be thought of as a distributed system with non-interactive workloads that involve many files. Grid computing is distinguished from conventional high-performance computing systems such as cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed (thus not physically coupled) than cluster computers. Although a single grid can be dedicated to a particular application, commonly a grid is used for a variety of purposes. Grids are often constructed with general-purpose grid middleware software libraries. Grid sizes can be quite large. Grids are a form of distributed computing composed of many networked loosely coupled computers acting together to perform large tasks. For certain applications, distributed or grid computing can be seen as a special type of parall

Official source

https://en.wikipedia.org/wiki/Grid_computing

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g-Social: Enhancing Integrated e-Science Tools with Social Networking Functionality

Andriani Stylianou

During the last decade, the scientific community has witnessed an unprecedented deployment of large-scale, federated e-Infrastructures such as Grid Computing, primarily for supporting data-intensive scientific exploration and coordinated problem solving. However, practical experience and user studies have indicated that the adoption of such e-Infrastructures is lagging behind original expectations, a fact which is mainly attributed to the limited support that available tools provide for user collaboration and information sharing. The goal of this paper is twofold, first to lay down the foundations for building a collaboration environment in the form of abstractions and second to show the effectiveness of these abstractions through g-Social, an Eclipse-based, open-source environment as an extension to g-Eclipse, that provides a powerful, user-friendly, platform-independent toolset for users, application developers and administrators of Grid infrastructures. g-Social enables user collaboration and resource sharing through Online Social Networking services, capitalizing on the success that these services have.

Ieee2012

The dissertation presents a new parallel programming paradigm for developing high performance (HPC) applications on the Grid. We address the question "How to tailor HPC applications to the Grid?" where the heterogeneity and the large scale of resources are the two main issues. We respond to the question at two different levels: the programming tool level and the parallelization concept level. At the programming tool level, the adaptation of applications to the Grid environment consists of two forms: either the application components should somehow decompose dynamically based on the available resources; or the components should be able to ask the infrastructure to select automatically the suitable resources by providing descriptive information about the resource requirements. These two forms of adaptation lead to the parallel object model on which resource requirements are integrated into shareable distributed objects under the form of object descriptions. We develop a tool called ParoC++ that implements the parallel object model. ParoC++ provides a comprehensive object-oriented infrastructure for developing and integrating HPC applications, for managing the Grid environment and for executing applications on the Grid. At the parallelization concept level, we investigate the parallelization scheme which provides the user a method to express the parallelism to satisfy the user specified time constraints for a class of problems with known (or well-estimated) complexities on the Grid. The parallelization scheme is constructed on the following two principal elements: the decomposition tree which represents the multi-level decomposition and the decomposition dependency graph which defines the partial order of execution within each decomposition. Through the scheme, the parallelism grain will be automatically chosen based on the available resources at run-time. The parallelization scheme framework has been implemented using the ParoC++. This framework provides a high level abstraction which hides all of the complexities of the Grid environment so that users can focus on the "logic" of their problems. The dissertation has been accompanied with a series of benchmarks and two real life applications from image analysis for real-time textile manufacturing and from snow simulation and avalanche warning. The results show the effectiveness of ParoC++ on developing high performance computing applications and in particular for solving the time constraint problems on the Grid.

EPFL2005

Interactivity on the Grid: Limitations and Opportunities

Marco Meoni

Grid computing has the intrinsic disadvantages of a batch system: the undetermined delay between the time a job is submitted and the time it is completed. Our approach to this problem is iGrid, a framework that proposes to change the Grid from a batch system to a more interactive distributed platform. Agents are deployed on nodes and wait to be contacted by an interactive job to start the computation, thus bypassing the regular Grid scheduler. A CPU fairshare mechanism allows users to get their fair iGrid machine share over a long period. Our prototype implementation scales to all 400 Grid nodes we were granted executing on top a software for data intensive parallel computing.

Acm Order Department, P O Box 64145, Baltimore, Md 21264 Usa2011

EPFL2005