Hou Bowen, Xu Dali, Fu Fangfa, Yang Bing, Niu Na
College of Computer and Control Engineering, Northeast Forestry University, Harbin 150040, China.
Department of Microelectronics Science and Technology, Harbin Institute of Technology, Harbin 150006, China.
Micromachines (Basel). 2025 Mar 31;16(4):421. doi: 10.3390/mi16040421.
In advanced multicore embedded systems, network-on-chip (NoC) is vital for core communication. With a rise in the number of cores, the incidence of core failures rises, potentially affecting system performance and stability. To address the challenges associated with core failures in network-on-chip (NoC) systems, researchers have proposed numerous topology reconfiguration algorithms. However, these algorithms fail to achieve an optimal balance between topology reconfiguration rate and recovery time. Addressing these issues, we propose an adaptive core distribution optimization topology reconfiguration algorithm, which involves the distribution of faulty cores as the main factor for the reconfiguration procedure. This algorithm is based on a 2D REmesh structure to achieve physical topology reconfiguration, optimized through a bidirectional search algorithm, and features an adaptive algorithm for optimizing core distribution. Experimental results show that a 96.70% successful reconfiguration rate with the proposed algorithm can be guaranteed when faulty cores are less than 68.75% of the max faulty cores. In particular, when the faulty cores reach 8 in the 8 × 9 REmesh, the successful reconfiguration rate is 63.60% with the proposed algorithm, which is 14.80% higher than BTTR and 9.30% higher than BSTR. Additionally, the average recovery time of our algorithm is reduced by 98.60% compared with BTTR and by 15.87% compared with BSTR, significantly improving both the performance and reliability in embedded systems.
在先进的多核嵌入式系统中，片上网络（NoC）对于内核通信至关重要。随着内核数量的增加，内核故障的发生率也会上升，这可能会影响系统性能和稳定性。为了应对片上网络（NoC）系统中与内核故障相关的挑战，研究人员提出了许多拓扑重新配置算法。然而，这些算法未能在拓扑重新配置速率和恢复时间之间实现最佳平衡。针对这些问题，我们提出了一种自适应内核分布优化拓扑重新配置算法，该算法将故障内核的分布作为重新配置过程的主要因素。该算法基于二维REmesh结构实现物理拓扑重新配置，通过双向搜索算法进行优化，并具有用于优化内核分布的自适应算法。实验结果表明，当故障内核少于最大故障内核的68.75%时，所提出的算法可以保证96.70%的成功重新配置率。特别是，当8×9的REmesh中故障内核达到8个时，所提出的算法的成功重新配置率为63.60%，比BTTR高14.80%，比BSTR高9.30%。此外，与BTTR相比，我们算法的平均恢复时间减少了98.60%，与BSTR相比减少了15.87%，显著提高了嵌入式系统的性能和可靠性。
