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Clustering Solutions of Multiobjective Function Inlining Problem

Authors Kateryna Muts , Heiko Falk

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Kateryna Muts
  • Hamburg University of Technology, Germany
Heiko Falk
  • Hamburg University of Technology, Germany

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Kateryna Muts and Heiko Falk. Clustering Solutions of Multiobjective Function Inlining Problem. In 21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023). Open Access Series in Informatics (OASIcs), Volume 114, pp. 4:1-4:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023) https://doi.org/10.4230/OASIcs.WCET.2023.4

Abstract

Hard real time-systems are often small devices operating on batteries that must react within a given deadline, so they must satisfy their timing, code size, and energy consumption requirements. Since these three objectives contradict each other, compilers for real-time systems go towards multiobjective optimizations which result in sets of trade-off solutions. A system designer can use the solution sets to choose the most suitable system configuration. Evolutionary algorithms can find trade-off solutions but the solution set might be large which complicates the task of the system designer. We propose to divide the solution set into clusters, so the system designer chooses the most suitable cluster and examines a smaller subset in detail. In contrast to other clustering techniques, our method guarantees that the sizes of all clusters are less than a predefined limit. Our method clusters a set by using any existing clustering method, divides clusters with sizes exceeding the predefined size into smaller clusters, and reduces the number of clusters by merging small clusters. The method guarantees that the final clusters satisfy the size constraint. We demonstrate our approach by considering a well-known compiler-based optimization called function inlining. It substitutes function calls by the function bodies which decreases the execution time and energy consumption of a program but increases its code size.

Subject Classification

ACM Subject Classification
  • Information systems → Clustering
  • Software and its engineering → Compilers
  • Computer systems organization → Real-time systems
  • Mathematics of computing → Evolutionary algorithms
Keywords
  • Clustering
  • multiobjective optimization
  • compiler
  • hard real-time system

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