ElCore: dynamic elastic resource management and discovery for future large-scale manycore enabled distributed systems

Javad Zarrin*, Rui L. Aguiar, João Paulo Barraca

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)221-239
Number of pages19
JournalMicroprocessors and Microsystems
Volume46
Issue numberPart B
Early online date22 Jun 2016
DOIs
Publication statusPublished - 1 Oct 2016
Externally publishedYes

Keywords

  • Resource allocation
  • Many-core
  • Many-Chip
  • HPC
  • Cluster
  • Grid
  • Cloud computing
  • Scheduling
  • Resource discovery
  • Resource utilization

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