Applying ASoC to Multi-core Applications for Workload Management

Zeppenfeld, Johannes; Bouajila, Abdelmajid; Stechele, Walter; Bernauer, Andreas; Bringmann, Oliver; Herkersdorf, Andreas

doi:10.1007/978-3-0348-0130-0_30

Cited by 10 publications

(2 citation statements)

References 8 publications

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“…The parameters for the algorithmic adaptations have to be defined by the application developer at designtime, for instance by using simulations. In contrast to Zeppenfeld et al [2011] our self-expression strategies do not yet include on-line learning. Moreover, we focus on heterogeneous multicore systems with a CPU and multiple reconfigurable hardware slots.…”

Section: Self-aware Computing Nodesmentioning

confidence: 91%

“…For instance, Zeppenfeld et al [2011] have developed an autonomic homogeneous multiprocessor system-on-chip architecture, where each processor is connected to several monitors, actuators and a single learning classifier table evaluator. The table stores condition-action rules where the fitness is learned at runtime using reinforcement learning.…”

Section: Self-aware Computing Nodesmentioning

confidence: 99%

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Self-Awareness as a Model for Designing and Operating Heterogeneous Multicores

Agne

Happe

Lösch

et al. 2014

ACM Trans. Reconfigurable Technol. Syst.

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Self-aware computing is a paradigm for structuring and simplifying the design and operation of computing systems that face unprecedented levels of system dynamics and thus require novel forms of adaptivity. The generality of the paradigm makes it applicable to many types of computing systems and, previously, researchers started to introduce concepts of self-awareness to multicore architectures. In our work we build on a recent reference architectural framework as a model for self-aware computing and instantiate it for an FPGA-based heterogeneous multicore running the ReconOS reconfigurable architecture and operating system. After presenting the model for self-aware computing and ReconOS, we demonstrate with a case study how a multicore application built on the principle of self-awareness, autonomously adapts to changes in the workload and system state. Our work shows that the reference architectural framework as a model for self-aware computing can be practically applied and allows us to structure and simplify the design process, which is essential for designing complex future computing systems. ACM Reference Format:Andreas Agne, Markus Happe, Achim Lösch, Christian Plessl, and Marco Platzner. 2014. Self-awareness as a model for designing and operating heterogeneous multicores.

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Section: Self-aware Computing Nodesmentioning

confidence: 91%

Section: Self-aware Computing Nodesmentioning

confidence: 99%