Search Results

Documents authored by Jadhav, Shashank

Document
DOI: 10.4230/OASIcs.WCET.2023.5
Efficient and Effective Multi-Objective Optimization for Real-Time Multi-Task Systems

Authors: Shashank Jadhav and Heiko Falk

Published in: OASIcs, Volume 114, 21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023)

Abstract
Embedded real-time multi-task systems must often not only comply with timing constraints but also need to meet energy requirements. However, optimizing energy consumption might lead to higher Worst-Case Execution Time (WCET), leading to an un-schedulable system, as frequently executed code can easily differ from timing-critical code. To handle such an impasse in this paper, we formulate a Metaheuristic Algorithm-based Multi-objective Optimization (MAMO) for multi-task real-time systems. But, performing multiple WCET, energy, and schedulability analyses to solve a MAMO poses a bottleneck concerning compilation times. Therefore, we propose two novel approaches - Path-based Constraint Approach (PCA) and Impact-based Constraint Approach (ICA) - to reduce the solution search space size and to cope with this problem. Evaluations showed that PCA and ICA reduced compilation times by 85.31% and 77.31%, on average, over MAMO. For all the task sets, out of all solutions found by ICA-FPA, on average, 88.89% were on the final Pareto front.
Cite as

Shashank Jadhav and Heiko Falk. Efficient and Effective Multi-Objective Optimization for Real-Time Multi-Task Systems. In 21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023). Open Access Series in Informatics (OASIcs), Volume 114, pp. 5:1-5:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{jadhav_et_al:OASIcs.WCET.2023.5,
  author =	{Jadhav, Shashank and Falk, Heiko},
  title =	{{Efficient and Effective Multi-Objective Optimization for Real-Time Multi-Task Systems}},
  booktitle =	{21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023)},
  pages =	{5:1--5:12},
  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.2023.5},
  URN =		{urn:nbn:de:0030-drops-184340},
  doi =		{10.4230/OASIcs.WCET.2023.5},
  annote =	{Keywords: Real-time systems, Multi-objective optimization, Metaheuristic algorithms, Compilers, Design space reduction}
}
Document
DOI: 10.4230/OASIcs.WCET.2023.6
Towards Multi-Objective Dynamic SPM Allocation

Authors: Shashank Jadhav and Heiko Falk

Published in: OASIcs, Volume 114, 21th International Workshop on Worst-Case Execution Time Analysis (WCET 2023)

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.
Cite as

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)

Copy BibTex To Clipboard

@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}
}
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact