Dynamic Resource Allocation In Embedded, High-performance And Cloud Computing by Leandro Soares IndrusiakDynamic Resource Allocation In Embedded, High-performance And Cloud Computing by Leandro Soares Indrusiak

Dynamic Resource Allocation In Embedded, High-performance And Cloud Computing

byLeandro Soares IndrusiakEditorPiotr Dziurzanski, Amit Kumar Singh

Hardcover | October 25, 2016

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The availability of many-core computing platforms enables a wide variety of technical solutions for systems across the embedded, high-performance and cloud computing domains. However, large scale many-core systems are notoriously hard to optimize. Choices regarding resource allocation alone can account for wide variability in timeliness and energy dissipation (up to several orders of magnitude).

Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computingcovers dynamic resource allocation heuristics for many-core systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonize the approaches to dynamic allocation across the complete spectrum between systems with little flexibility and strict real-time guarantees all the way to highly dynamic systems with soft performance requirements.

Technical topics presented in the book include:
• Load and Resource Models
• Admission Control
• Feedback-based Allocation and Optimization
• Search-based Allocation Heuristics
• Distributed Allocation based on Swarm Intelligence
• Value-Based Allocation

Each of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip many-core processors, grids and private cloud environments.
Leandro Soares Indrusiak
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Title:Dynamic Resource Allocation In Embedded, High-performance And Cloud ComputingFormat:HardcoverDimensions:160 pages, 9.41 × 7.24 × 0.98 inPublished:October 25, 2016Publisher:River PublishersLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:8793519087

ISBN - 13:9788793519084

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