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.
@InProceedings{jadhav_et_al:OASIcs.WCET.2023.6, author = {Jadhav, Shashank and Falk, Heiko}, title = {{Towards Multi-Objective Dynamic SPM Allocation}}, booktitle = {21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023)}, pages = {6:1--6:12}, series = {Open Access Series in Informatics (OASIcs)}, ISBN = {978-3-95977-293-8}, ISSN = {2190-6807}, year = {2023}, volume = {114}, editor = {W\"{a}gemann, Peter}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.WCET.2023.6}, URN = {urn:nbn:de:0030-drops-184353}, doi = {10.4230/OASIcs.WCET.2023.6}, annote = {Keywords: Multi-objective optimization, Embedded systems, Compilers, Dynamic SPM allocation, Metaheuristic algorithms} }
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