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Grid-enabling complex system applications with QosCosGrid: an architectural perspective

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TLDR
This work designs architecture for a quasi-opportunistic supercomputer within the EU-supported project QosCosGrid, and presents the results obtained from studying and identifying the requirements a grid needs to meet in order to facilitate quasi- opportunistic supercomputing.
Abstract
Grids are becoming mission-critical components in research and industry, offering sophisticated solutions in leveraging large-scale computing and storage resources. Grid resources are usually shared among multiple organizations in an opportunistic manner. However, an opportunistic or "best effort" quality-of-service scheme may be inadequate in situations where a large number of resources need to be allocated and applications which rely on static, stable execution environments. The goal of this work is to implement what we refer to as quasi-opportunistic supercomputing. A quasi-opportunistic supercomputer facilitates demanding parallel computing applications on the basis of massive, non-dedicated resources in grid computing environments. Within the EU-supported project QosCosGrid we are developing a quasi-opportunistic supercomputer. In this work we present the results obtained from studying and identifying the requirements a grid needs to meet in order to facilitate quasi-opportunistic supercomputing. Based on these requirements we have designed architecture for a quasi-opportunistic supercomputer. The paper presents and discusses this architecture.

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Citations
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Performance of distributed multiscale simulations

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Book ChapterDOI

Complex System Simulations with QosCosGrid

TL;DR: The middleware developed in the QosCosGrid project is described, which provides advance reservation and resource co-allocation functionality as well as support for parallel applications based on OpenMPI (for C/C++ and Fortran) or ProActive for Java.
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A Principled Approach to Distributed Multiscale Computing, from Formalization to Execution

TL;DR: A principled approach to distributed multiscales computing is taken, formalizing multiscale modeling based on natural processes and extending the Multiscale Modeling Language as a clear, general, formal, and high-level means to specify scales and interactions.
References
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Journal ArticleDOI

The GRID: Blueprint for a New Computing Infrastructure

TL;DR: The main purpose is to update the designers and users of parallel numerical algorithms with the latest research in the field and present the novel ideas, results and work in progress and advancing state-of-the-art techniques in the area of parallel and distributed computing for numerical and computational optimization problems in scientific and engineering application.
Journal ArticleDOI

A taxonomy and survey of grid resource management systems for distributed computing

TL;DR: In this article, an abstract model and a comprehensive taxonomy for describing resource management architectures is developed, which is used to identify approaches followed in the implementation of existing resource management systems for very large-scale network computing systems known as Grids.
Journal ArticleDOI

Parsec: a parallel simulation environment for complex systems

TL;DR: The simulation environment the authors developed at UCLA attempts to address some of the issues facing widespread use of parallel simulation, including a lack of tools for integrating parallel model execution into the overall framework of system simulation.
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