Task mapping and routing are crucial steps in the Networks on Chip (NoC) based Multiprocessor System on Chip (MPSoC) design. While the mapping must ensure an optimized arrangement of the applications’ tasks on the system cores, the routing must ensure the tasks’ communication with the minimum possible delay. We observe that these two problems are highly dependent since finding a routing solution requires first finding a mapping solution. Based on that, this paper analyzes the mapping and routing problems in NoC-based MPSoC and defines a joint version as the Mapping and Routing Problem (MRP). We propose a mathematical model that generates mapping and routing solutions based on a specific bandwidth of NoC links. We also propose three evolutionary metaheuristic algorithms to find optimized solutions to the MRP: Genetic (GA), Memetic (MA), and Transgenetic Algorithms (TA). Experimental results evaluating communication latency demonstrate that the proposed algorithms suit well for the tackled problem, but the TA stands out among all the compared solutions. Overall, TA achieved up to 8% and 19% better performance than the compared algorithms in Global Average Delay and Maximum Delay. Also, it outperformed the other strategies in 55.76% and 51.58% of all the performed simulations in both respective metrics.

任务映射和路由是基于片上网络 (NoC) 的多处理器片上系统 (MPSoC) 设计中的关键步骤。虽然映射必须确保应用程序任务在系统核心上的优化安排，但路由必须确保任务通信以尽可能小的延迟进行。我们观察到这两个问题是高度相关的，因为找到路由解决方案需要首先找到映射解决方案。在此基础上，本文分析了基于NoC的MPSoC中的映射和路由问题，定义了一个联合版本作为映射和路由问题(MRP)。我们提出了一种数学模型，该模型基于 NoC 链路的特定带宽生成映射和路由解决方案。我们还提出了三种进化元启发式算法来寻找 MRP 的优化解决方案：遗传 (GA)、模因 (MA)、和转基因算法（TA）。评估通信延迟的实验结果表明，所提出的算法非常适合解决的问题，但 TA 在所有比较的解决方案中脱颖而出。总体而言，TA 在全局平均延迟和最大延迟方面的性能比比较算法高出 8% 和 19%。此外，它在所有执行的模拟中分别以 55.76% 和 51.58% 的成绩优于其他策略。