Meeting Job-Level Dependencies by Task Merging

• Published in: Proceedings of the ASP-DAC ... Asia and South Pacific Design Automation Conference pp. 792 - 798
• Main Author: Becker, Matthias
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22.01.2024
• Subjects: Constraint handling; Design automation; Job shop scheduling; Merging; Runtime; Scalability; Scheduling algorithms
• ISSN: 2153-697X
• DOI: 10.1109/ASP-DAC58780.2024.10473901

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.