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Time, Energy and Security Analysis for Multi-/Many-Core heterogeneous Platforms (TeamPlay)
Fact Sheet
| Acronym | TeamPlay |
|---|---|
| Name | Time, Energy and Security Analysis for Multi-/Many-Core heterogeneous Platforms |
| Homepage | teamplay-h2020.eu |
| Role of TUHH | Work Package Leader |
| Start Date | 01/01/2018 |
| End Date | 30/06/2021 |
| Funds Donor | European Commission (Horizon 2020) |
Summary
The TeamPlay project aims to develop new, formally-motivated, techniques that will allow execution time, energy usage, security, and other important non-functional properties of parallel software to be treated effectively, and as first-class citizens. We will build this into a toolbox for developing highly parallel software for low-energy systems, as required by the internet of things, cyber-physical systems etc. The TeamPlay approach will allow programs to reflect directly on their own time, energy consumption, security, etc., as well as enabling the developer to reason about both the functional and the non-functional properties of their software at the source code level.
Our success will ensure significant progress on a pressing problem of major industrial importance: how to effectively manage energy consumption for parallel systems while maintaining the right balance with other important software metrics, including time, security etc. The project brings together leading industrial and academic experts in parallelism, energy modeling/transparency, worst-case execution time analysis, non-functional property analysis, compilation, security, and task coordination. Results will be evaluated using industrial use cases taken from the computer vision, satellites, flying drones, medical and cybersecurity domains.
TeamPlay Publications of the Embedded Systems Design Group
| [183642] |
| Title: Efficient and Effective Multi-Objective Optimization for Real-Time Multi-Task Systems. <em>In Proceedings of the 21st International Workshop on Worst-Case Execution Time Analysis (WCET)</em> |
| Written by: Shashank Jadhav and Heiko Falk |
| in: July (2023). |
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| on pages: 5:1-5:12 |
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| Address: Vienna / Austria |
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| ISBN: 10.4230/OASIcs.WCET.2023.5 |
| how published: 23-75 JF23a WCET |
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Note: sjadhav, hfalk, teamplay, ESD, WCC
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.