Near-optimal deployment of dataflow applications on many-core platforms with real-time guarantees

• Published in: Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 pp. 752 - 757
• Main Authors: Skalistis, Stefanos, Simalatsar, Alena
• Format: Conference Proceeding
• Language: English
• Published: EDAA 01.03.2017
• Subjects: Computational modeling; Data models; Delays; Optimization; Real-time systems; Resource management; Scheduling
• ISSN: 1558-1101
• DOI: 10.23919/DATE.2017.7927090

Safe and optimal deployment of data-streaming applications on many-core platforms requires the realistic estimation of task Worst-Case Execution Time (WCET). On the other hand, task WCET depends on the deployment solution, due to the varying number of interferences on shared resources, thus introducing a cyclic dependency. Moreover, WCET is still an over-approximation of the Actual Execution Time (AET), thus leaving room for run-time optimisation. In this paper we introduce an offline/online optimisation approach. In the offline phase, we first break the cyclic dependency and acquire safe and near-optimal solutions for tasks partitioning/placement, mapping, scheduling and buffer allocation. Then, we tighten the WCETs and update the scheduling function accordingly. In the online phase we introduce a safe distributed readjustment of the offline schedule, based on the AET. Experiments on a Kalray MPPA-256 platform show a tightening of the guaranteed latency up to 46% in the offline phase, and 41% latency reduction in the online phase. In total, we achieve more than 50% of latency reduction.