Meeting Job-Level Dependencies by Task Merging

Industrial applications are often time critical and subject to end-to-end latency constraints. Job-level dependencies can be leveraged to specify a partial ordering on tasks' jobs already at early design phases, agnostic of the hardware platform or scheduling algorithm, and guarantee that end-t...

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Veröffentlicht in:Proceedings of the ASP-DAC ... Asia and South Pacific Design Automation Conference S. 792 - 798
1. Verfasser: Becker, Matthias
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 22.01.2024
Schlagworte:
Constraint handling
Design automation
Job shop scheduling
Merging
Runtime
Scalability
Scheduling algorithms
ISSN:2153-697X
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Beschreibung
Zusammenfassung:Industrial applications are often time critical and subject to end-to-end latency constraints. Job-level dependencies can be leveraged to specify a partial ordering on tasks' jobs already at early design phases, agnostic of the hardware platform or scheduling algorithm, and guarantee that end-to-end latency constraints of task chains are met as long as the job-level dependencies are respected. However, their realization at runtime can introduce overheads and complicates the scheduling and timing analysis. This work presents an approach that merges multi-periodic tasks that are connected by job-level dependencies to a single task. A Constraint Programming formulation is presented that optimally merges such task clusters while all job-level dependencies are respected. Such an approach removes the need to consider job-level dependencies at runtime without being bound to a specific scheduling algorithm. Evaluations highlight the applicability of the approach by system-level experiments and showcase the scalability of the approach using synthetic task clusters.
ISSN:2153-697X
DOI:10.1109/ASP-DAC58780.2024.10473901