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Title: Multiobjective code compression and function inlining for hard real-time systems
Language: English
Authors: Muts, Kateryna  
Keywords: Compiler-based optimization; Function Inlining; Machine learning; Search space reduction; Hard real-time system
Issue Date: 26-Jan-2023
Abstract (english): 
Compiler-based optimizations are efficient techniques to improve a program to be compiled. Function inlining is a well-known compiler-based optimization that substitutes function calls by the body of the function. The data represent the results of multiobjective function inlining for hard real-time systems with code size, energy consumption and worst-case execution time (WCET) as objectives. Since the analyses of energy consumption and WCET are very time-consuming at compile time, search space reduction and predictions based on machine learning techniques were applied to speed up the multiobjective function inlining at compile time.
DOI: 10.15480/336.4890
Institute: Eingebettete Systeme E-13 
Document Type: Dataset
Project: Multikriterielle Code-Optimierung für Eingebettete Harte Echtzeitsysteme 
Funded by: Deutsche Forschungsgemeinschaft (DFG) 
License: CC0 1.0 (Public Domain Dedication) CC0 1.0 (Public Domain Dedication)
Is supplement to: 10.15480/882.4799
Is compiled by: 10.1007/s11241-010-9101-x
Appears in Collections:Research Data TUHH

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