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ElCOre: Dynamic elastic resource management and discovery for future large-scale manycore enabled distributed systems

机译:ElCOre:动态弹性资源管理和发现,用于未来的大规模多核启用分布式系统

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摘要

Large-scale computing environments (such as HPC Clusters, Grids and Clouds) provide a vast number of heterogeneous resources (such as computing, storage, data and network resources) for the users/machines with various types of accessibility (in terms of resource, data, service and application). Resource management is one of the most significant underlying challenges for efficient resource sharing and utilization in such computing environments. Designing a resource management model which can be applied and adjusted to the requirements of these different future complex computing environments is an extra challenge. This paper will address the problem of resource management for the future large-scale many-core enabled computing environments by focusing on resource allocation issues. It provides a fully decentralized generic resource management architecture which can be applied to such distributed environments. Simulation results prove that our resource management scheme is highly scalable and provides a high level of accuracy for resource allocation which has a significant impact on the overall system performance. (C) 2016 Elsevier B.V. All rights reserved.
机译:大型计算环境(例如HPC群集,网格和云)为具有各种可访问性(就资源而言,数据,服务和应用程序)。资源管理是在这样的计算环境中进行有效资源共享和利用的最重大的基础挑战之一。设计可应用于和适应这些不同的未来复杂计算环境要求的资源管理模型是一个额外的挑战。本文将通过关注资源分配问题来解决未来的大规模多核启用计算环境的资源管理问题。它提供了完全分散的通用资源管理体系结构,可以将其应用于此类分布式环境。仿真结果表明,我们的资源管理方案具有高度的可扩展性,并为资源分配提供了很高的准确性,这对整个系统的性能有重大影响。 (C)2016 Elsevier B.V.保留所有权利。

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