The increasing availability of different kinds of processing resources in heterogeneous system architectures associated with today's fast-changing, unpredictable workloads has propelled an interest towards systems able to dynamically and autonomously adapt how computing resources are exploited to optimize a given goal. Self-adaptiveness and hardware-assisted virtualization are the two key-enabling technologies for this kind of architectures, to allow the efficient exploitation of the available resources based on the current working context. The SAVE project will develop HW/SW/OS components that allow for deciding at runtime the mapping of the computation kernels on the appropriate type of resource, based on the current system context and requirements.

Runtime Resource Management in Heterogeneous System Architectures: The SAVE Approach

DURELLI, GIANLUCA CARLO;POGLIANI, MARCELLO;MIELE, ANTONIO ROSARIO;SANTAMBROGIO, MARCO DOMENICO;BOLCHINI, CRISTIANA
2014

Abstract

The increasing availability of different kinds of processing resources in heterogeneous system architectures associated with today's fast-changing, unpredictable workloads has propelled an interest towards systems able to dynamically and autonomously adapt how computing resources are exploited to optimize a given goal. Self-adaptiveness and hardware-assisted virtualization are the two key-enabling technologies for this kind of architectures, to allow the efficient exploitation of the available resources based on the current working context. The SAVE project will develop HW/SW/OS components that allow for deciding at runtime the mapping of the computation kernels on the appropriate type of resource, based on the current system context and requirements.
Proc. IEEE Int. Symp. Parallel and Distributed Processing with Applications (ISPA)
978-147994293-0
resource allocation; virtualisation; SAVE approach; heterogeneous system architecture; performance-energy trade-off; processing elements; resource allocation policy; runtime resource management; self-adaptive systems; self-adaptive virtualisation-aware high- performance-low-energy heterogeneous system architecture; system resources; Actuators; Computer architecture; Graphics processing units; Monitoring; Optimization; Resource management; Runtime; Heterogeneous systems; Virtualization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/865797
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