46 research outputs found

    Containers : A Sound Basis For a True Single System Image

    Get PDF
    Clusters of SMPs are attractive for executing shared memory parallel applications but reconciling high performance and ease of programming remains an open issue. A possible approach is to provide an efficient Single System Image (SSI) operating system giving the illusion of an SMP machine. In this paper, we introduce the concept of container as a mechanism to unify global resource management at the lowest operating system level. Higher level operating system services such as virtual memory system and file cache can be easily implemented based on containers and transparently take benefit of the whole memory resource available in the cluster

    Open Source Solutions for Optimization on Linux Clus- ters

    Get PDF
    Abstract: Parallel implementation of optimization algorithms is an alternative and effective paradigm to speed up the search for solutions of optimization problems. Currently a Linux Cluster is probably the best technological solution available considering both the overall system performance and its cost. Open Source community offers to researchers a set of software tools for setting up clusters and to optimize their performance. The aim of this paper is to review the open source tools are useful to build a cluster which efficiently runs parallel optimization algorithms. Particular attention is given to the OpenMosix approach to scalable computing. Keywords: Open Source, Linux Cluster, Optimization, OpenMosix, Dynamic Load Balancing INTRODUCTION Although (sequential) optimization algorithms have reached a sophisticated level of implementation allowing good computational results for a large variety of optimization problems, usually the running time required to explore the solution space associated to optimization problems can be very large With the diffusion of parallel computers and fast communication networks, parallel implementation of optimization algorithms can be an alternative and effective paradigm to speed up the search for solutions of optimization problems

    A Computational Economy for Grid Computing and its Implementation in the Nimrod-G Resource Brok

    Full text link
    Computational Grids, coupling geographically distributed resources such as PCs, workstations, clusters, and scientific instruments, have emerged as a next generation computing platform for solving large-scale problems in science, engineering, and commerce. However, application development, resource management, and scheduling in these environments continue to be a complex undertaking. In this article, we discuss our efforts in developing a resource management system for scheduling computations on resources distributed across the world with varying quality of service. Our service-oriented grid computing system called Nimrod-G manages all operations associated with remote execution including resource discovery, trading, scheduling based on economic principles and a user defined quality of service requirement. The Nimrod-G resource broker is implemented by leveraging existing technologies such as Globus, and provides new services that are essential for constructing industrial-strength Grids. We discuss results of preliminary experiments on scheduling some parametric computations using the Nimrod-G resource broker on a world-wide grid testbed that spans five continents

    OPEN CHARM IN PROTON-LEAD COLLISIONS WITH ALICE

    Get PDF
    2003/2004XVII Ciclo1974Versione digitalizzata della tesi di dottorato cartacea

    Deploying and Maintaining a Campus Grid at Clemson University

    Get PDF
    Many institutions have all the tools needed to create a local grid that aggregates commodity compute resources into an accessible grid service, while simultaneously maintaining user satisfaction and system security. In this thesis, the author presents a three-tiered strategy used at Clemson University to deploy and maintain a grid infrastructure by making resources available to both local and federated remote users for scientific research. Using this approach virtually no compute cycles are wasted. Usage trends and power consumption statistics collected from the Clemson campus grid are used as a reference for best-practices. The loosely-coupled components that comprise the campus grid work together to form a highly cohesive infrastructure that not only meets the computing needs of local users, but also helps to fill the needs of the scientific community at large. Experience gained from the deployment and management of this system may be adapted to other grid sites, allowing for the development of campus-wide, grid-connected cyberinfrastructures
    corecore