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Cyber Physical Systems (CPS) are typically implemented on multicore platforms to handle computational pressure and performance requirements. Complex data flows in those applications cause contention among networked processors, resulting in unpredictable performance. In this work, we explore the impact of application mapping on network contention and predictability. A mapping algorithm focusing on...
Contiguous processor allocation improves both the network and the application performance, by decreasing the congestion probability among communication of different applications. Consequently, the average, standard deviation and worst-case latency of the network is decreased significantly. This makes the contiguous allocation a good solution for time-critical applications with bounded deadlines. On...
The importance of first node selection in run-time resource management is shown in our previous work, SHiC. It is desired in SHiC to find the optimum node in an agile manner. Accordingly, the current mapping picture of the system is simplified to SHiC by modeling each application as a rectangle of occupied nodes. However, the algorithm performance can be influenced significantly with the rectangle...
A system-level approach to fault-aware resource management of many-core systems is proposed. The proposed approach, called SHiFA, is able to tolerate run-time faults at system level without any hardware overhead. In contrast to the existing system-level methods, network resources are also considered to be potentially faulty. Accordingly, applications are mapped onto healthy nodes of the system at...
In this paper, we propose a run-time mapping algorithm, CASqA, for networked many-core systems. In this algorithm, the level of contiguousness of the allocated processors (α) can be adjusted in a fine-grained fashion. A strictly contiguous allocation (α = 0) decreases the latency and power dissipation of the network and improves the applications execution time. However, it limits the achievable throughput...
Stochastic hill climbing algorithm is adapted to rapidly find the appropriate start node in the application mapping of network-based many-core systems. Due to highly dynamic and unpredictable workload of such systems, an agile run-time task allocation scheme is required. The scheme is desired to map the tasks of an incoming application at run-time onto an optimum contiguous area of the available nodes...
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