Mapping algorithm which means which core should be linked to which router is one of the key issues in the design flow of network-on-chip. To achieve an application-specific NoC design procedure that minimizes the communication cost and improves the fault tolerant property, first a heuristic mapping algorithm that produces a set of different mappings in a reasonable time is presented. This algorithm allows the designers to identify the set of most promising solutions in a large design space, which has low communication costs while yielding optimum communication costs in some cases. Another evaluated parameter, vulnerability index, is then considered as a principle of estimating the fault-tolerance property in all produced mappings. Finally, in order to yield a mapping which considers trade-offs between these two parameters, a linear function is defined and introduced. It is also observed that more flexibility to prioritize solutions within the design space is possible by adjusting a set of if-then rules in fuzzy logic.
Network-on-Chips (NoCs) usually use regular mesh-based topologies. Regular mesh topologies are not always efficient because of power and area constraints which should be considered in designing system-on-chips. To overcome this problem, irregular mesh NoCs are used for which the design of routing algorithms is an important issue. This paper presents a novel routing algorithm for irregular mesh-based NoCs called "i-route". In contrast to other routing algorithms, this algorithm can be implemented on any arbitrary irregular mesh NoC without any change in the place of IPs. In this algorithm, messages are routed using only 2 classes of virtual channels. Simulation results show that using only 2 virtual channels, "iroute" exhibits a better performance compared to other algorithms already proposed in the same context.
In this paper, a novel procedure is introduced to find an optimal application-specific Network on Chip, considering communication cost and fault-tolerant requirements. The procedure, which is called Ruby, uses a genetic algorithm and a mapping solution to generate a wide range of mappings. A designer can select the optimal mapping from those generated ones, using either a linear function or the fuzzy logic. Ruby enables the designer to customize and prioritize the communication cost and the robustness index. The experimental results reveal the capability of the proposed procedure to explore the design space and assist a designer to find the appropriate mapping from numerous generated solutions.
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