Near-optimal deployment of dataflow applications on many-core platforms with real-time guarantees
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 introduc...
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Published in | Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 pp. 752 - 757 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
Published |
EDAA
01.03.2017
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 1558-1101 |
DOI: | 10.23919/DATE.2017.7927090 |