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Title: Hardware-accelerated evolutionary hard real-time task mapping for wormhole network-on-chip with priority-preemptive arbitration
Author: Ma, Yunfeng
ISNI:       0000 0004 7226 9439
Awarding Body: University of York
Current Institution: University of York
Date of Award: 2016
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Network-on-Chip (NoC) is an alternative on-chip interconnection paradigm to replace existing ones such as Point-to-Point and shared bus. NoCs designed for hard real-time systems need to guarantee the system timing performance, even in the worst-case scenario. A carefully planned task mapping which indicates how tasks are distributed on a NoC platform can improve or guarantee their timing performance. While existing offline mapping optimisations can satisfy timing requirements, this is obtained by sacrificing the flexibility of the system. In addition, the design exploration process will be prolonged with the continuous enlargement of the design space. Online mapping optimisations, by contrast, are affected by low success rates for remapping or a lack of guarantee of systems timing performance after remapping, especially in hard real-time systems. The existing limitations therefore motivate this research to concentrate on the mapping optimisation of real-time NoCs, and specifically dynamic task allocation in hard real-time systems. Four techniques and implementations are proposed to address this issue. The first enhances the evaluation efficiency of a hard real-time evaluation method from a theoretical point of view. The second technique addresses the evaluation efficiency from a practical point of view to enable online hard real-time timing analysis. The third technique advocates a dynamic mapper to enhance the remapping success rate with the accelerated model and architecture. The final technique yields a dynamic mapping algorithm that can search schedulable task allocation for hard real-time NoCs at run time, while simultaneously reducing the task migration cost after remapping.
Supervisor: Indrusiak, Leandro Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available