Error-Based Metric for Cross-Layer Cut Determination

Rafiev, A; Xia, F; Iliasov, A; Gensh, R; Aalsaud, A; Romanovsky, A; Yakovlev, A

doi:10.1007/978-3-319-62920-9_4

Error-Based Metric for Cross-Layer Cut Determination

Lookup NU author(s): Dr Ashur Rafiev, Dr Fei Xia, Dr Alexei Iliasov, Dr Rem Gensh, Ali Aalsaud, Emeritus Professor Alexander Romanovsky ORCiD, Professor Alex Yakovlev

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This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by Springer Verlag, 2018.

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Abstract

© 2018, Springer International Publishing AG. With the increase of system complexity in both platforms and applications, power modelling of heterogeneous systems is facing grand challenges from the model scalability issue. To address these challenges, this chapter studies two systematic methods: selective abstraction and stochastic techniques. The concept of selective abstraction via black-boxing is realised using hierarchical modelling and cross-layer cuts, respecting the concepts of boxability and error contamination. The stochastic aspect is formally underpinned by Stochastic Activity Networks (SANs). The proposed method is validated with experimental results from Odroid XU3 heterogeneous 8-core platform and is demonstrated to maintain high accuracy while improving scalability.