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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 manycore systems are notoriously hard to optimise. 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 Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to
harmonise 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 Optimisation
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 manycore processors, grids and private cloud environments.
List of contents
Dynamic Resource Allocation in Embedded, High-Performance and Cloud Computing
About the author
Leandro Soares Indrusiak is a faculty member in the Department of Com- puter Science at the University of York. He is part of the Real-Time Systems group, with technical contributions in the areas of systems and networks with timing and energy constraints. He has more than 100 peer-reviewed publications in the top conferences and journals in real-time and embedded systems, design automation and high-performance computing. Over the past decade, he has supervised and graduated seven doctoral students, has held visiting faculty positions in five different countries, and has led projects funded by the European Union, research councils of the UK, Germany and Brazil, as well as several companies. Dr Indrusiak holds a bi-national doctoral degree jointly issued by UFRGS (Brazil) and TU Darmstadt (Germany) in 2003, is a member of the European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), and a senior member of the IEEE.
Summary
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 manycore systems are notoriously hard to optimise. 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 Computing covers dynamic resource allocation heuristics for manycore systems, aiming to provide appropriate guarantees on performance and energy efficiency. It addresses different types of systems, aiming to harmonise 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 Optimisation• Search-based Allocation Heuristics• Distributed Allocation based on Swarm Intelligence• Value-Based AllocationEach of the topics is illustrated with examples based on realistic computational platforms such as Network-on-Chip manycore processors, grids and private cloud environments.
