Approximating WCET and Energy Consumption for Fast Multi-Objective Memory Allocation

Author:

Jadhav Shashank1,Falk Heiko1

Affiliation:

1. Institute of Embedded Systems, Hamburg University of Technology (TUHH), Germany

Funder

European Union's Horizon 2020 Research and Innovation Programme

Publisher

ACM

Reference29 articles.

1. AbsInt Angewandte Informatik GmbH. 2021. aiT Worst-Case Execution Time Analyzers. AbsInt Angewandte Informatik GmbH. 2021. aiT Worst-Case Execution Time Analyzers.

2. Optimal code layout for reducing energy consumption in embedded systems

3. Armelle Bonenfant , Denis Claraz , Marianne De Michiel , and Pascal Sotin . 2017 . Early WCET prediction using machine learning . In 17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik. Armelle Bonenfant, Denis Claraz, Marianne De Michiel, and Pascal Sotin. 2017. Early WCET prediction using machine learning. In 17th International Workshop on Worst-Case Execution Time Analysis (WCET 2017). Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik.

4. Heiko Falk , Sebastian Altmeyer , Peter Hellinckx , Björn Lisper , Wolfgang Puffitsch , Christine Rochange , Martin Schoeberl , Rasmus Bo Sørensen , Peter Wägemann , and Simon Wegener . 2016 . TACLeBench: A benchmark collection to support worst-case execution time research . In 16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016). Schloss Dagstuhl-Leibniz-Zentrum für Informatik. Heiko Falk, Sebastian Altmeyer, Peter Hellinckx, Björn Lisper, Wolfgang Puffitsch, Christine Rochange, Martin Schoeberl, Rasmus Bo Sørensen, Peter Wägemann, and Simon Wegener. 2016. TACLeBench: A benchmark collection to support worst-case execution time research. In 16th International Workshop on Worst-Case Execution Time Analysis (WCET 2016). Schloss Dagstuhl-Leibniz-Zentrum für Informatik.

5. Optimal static WCET-aware scratchpad allocation of program code

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