2026-09-10T02:25:53Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:18435 2026-09-05T14:59:40Z ddc:004 open_access

Towards Multi-Objective Dynamic SPM Allocation Jadhav, Shashank Falk, Heiko Multi-objective optimization Embedded systems Compilers Dynamic SPM allocation Metaheuristic algorithms Most real-time embedded systems are required to fulfill timing constraints while adhering to a limited energy budget. Small ScratchPad Memory (SPM) poses a common hardware constraint on embedded systems. Static SPM allocation techniques are limited by the SPM’s stringent size constraint, which is why this paper proposes a Dynamic SPM Allocation (DSA) model at the compiler level for the dynamic allocation of a program to SPM during runtime. To minimize Worst-Case Execution Time (WCET) and energy objectives, we propose a multi-objective DSA-based optimization. Static SPM allocations might inherently use SPM sub-optimally, while all proposed DSA optimizations are only single-objective. Therefore, this paper is the first step towards a DSA that trades WCET and energy objectives simultaneously. Even with extra DSA overheads, our approach provides better quality solutions than the state-of-the-art multi-objective static SPM allocation and ILP-based single-objective DSA approach. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Shashank Jadhav and Heiko Falk 2023 Is Part Of OASIcs, Volume 114, 21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/OASIcs.WCET.2023.6 urn:nbn:de:0030-drops-184353 https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2023.6 eng https://creativecommons.org/licenses/by/4.0/legalcode