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Lookup NU author(s): Dr Ashur Rafiev, Dr Fei Xia, Dr Alexei Iliasov, Rem Gensh, Ali Aalsaud, Emeritus Professor Alexander RomanovskyORCiD, Professor Alex Yakovlev
Traditional hierarchical modelling methods tend to have layers of abstraction corresponding to naturally existing layers of concern in multilevel systems. Although convenient, this is not always optimal for analysis and design. For instance, parts of a system which are in the same layer may not contribute to the same degree on some metric, e.g. system power consumption. To moderate the modelling, analysis and design effort, and potentially runtime control overhead for models used at runtime, less significant parts of the system should be studied at higher levels of abstraction and more significant ones with more detail. Concentrating on system power consumption, this paper presents Order Graphs (OGs), which have a clear hierarchical structure, but provide straightforward vertical zooming across multiple layers (orders) of model fidelity, resulting in the discovery of power-proportional cuts that run through different orders to be analysed together in a flat manner. Stochastic Activity Networks (SANs), a good flat modelling method, is suggested as an example of studying technique for cuts discovered with OGs. A series of experiments on an Odroid development system consisting of an ARM big.LITTLE multi-core structure provides initial validation for the approach.
Author(s): Rafiev A, Xia F, Iliasov A, Gensh R, Aalsaud A, Romanovsky A, Yakovlev A
Publication type: Report
Publication status: Published
Series Title: School of Computing Science Technical Report Series
Year: 2015
Pages: 10
Online publication date: 01/01/2015
Report Number: 1443
Institution: School of Computing Science, University of Newcastle upon Tyne
Place Published: Newcastle upon Tyne
URL: http://www.cs.ncl.ac.uk/publications/trs/papers/1443.pdf
