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Towards Multi-Objective Dynamic SPM Allocation

Authors Shashank Jadhav , Heiko Falk

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Author Details

Shashank Jadhav
  • Hamburg University of Technology, Germany
Heiko Falk
  • Hamburg University of Technology, Germany

Funding

This work is part of a project that received funding from NXP Semiconductors.

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Shashank Jadhav and Heiko Falk. Towards Multi-Objective Dynamic SPM Allocation. In 21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023). Open Access Series in Informatics (OASIcs), Volume 114, pp. 6:1-6:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/OASIcs.WCET.2023.6

Abstract

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.

Subject Classification

ACM Subject Classification
  • Computer systems organization → Real-time systems
  • Software and its engineering → Compilers
  • Mathematics of computing → Discrete mathematics
Keywords
  • Multi-objective optimization
  • Embedded systems
  • Compilers
  • Dynamic SPM allocation
  • Metaheuristic algorithms

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