.png){kind=icon}
Return
Efficient application mapping approach based on grey wolf optimization for network on chip
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jnca.2023.103729.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In modern chip designs with multiple processors, network-on-chip (NoC) has emerged as a critical solution, offering scalability, flexibility, modularity, and efficiency. However, a significant challenge in application mapping is minimizing communication costs as they directly affect performance and energy consumption. Although several mapping algorithms have been developed, they often suffer from complexity, suboptimal performance, and slow convergence. To address these challenges, this paper proposes a novel approach for mapping using the grey wolf optimization (GWO) technique inspired by nature. The proposed GWO-based map -ping approach for NoC (GNoC) is augmented with an effective clustering-based initial mapping strategy, further enhancing its capabilities. Furthermore, a second heuristic algorithm is introduced, incorporating a modified GWO method with polynomial regression (GNoC-PR). This modification optimizes the runtime efficiency and enhances the overall mapping quality. The proposed method was evaluated through comprehensive simulations and compared with state-of-the-art solutions. The results demonstrate that the proposed algorithm outperforms existing methods in several key metrics, including a power consumption reduction of 19.7%, energy efficiency improvement of 17%, and a significant 40% decrease in computational overhead on average. To validate the effectiveness of our mapping technique, we evaluated both embedded and synthetic applications, considering various metrics such as communication cost, average network latency, and power consumption.
Keywords:
Network-on-chip
Application mapping
Grey wolf optimization
Clustering
Polynomial regression
Convergence
Journal
IF:
8
Papers:
3.7K
Citations:
1.1W
Organization
Cited Papers
ShareSaveNoC2: An Efficient Interfacing Approach for Heavily-Communicating NoC-Based Systems.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAIShareSaveShareSave
ShareSaveShareSaveBandwidth-Constrained Multi-Objective Segmented Brute-Force Algorithm for Efficient Mapping of Embedded Applications on NoC ArchitectureIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSavePerformance Evaluation of Application Mapping Approaches for Network-on-Chip DesignsIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAIShareSaveShareSave
View more