.png){kind=icon}
返回
Application Mapping Using Cuckoo Search Optimization With Levy Flight for NoC-Based System
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2021.3120079.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Network on chip (NoC) is a promising communication infrastructure for multiple cores on a chip to exchange data efficiently. In such NoC architecture, application mapping is a process of assigning tasks to the processing cores. An optimized application mapping technique enhances the performance of a chip and reduces the entire chip's energy consumption. The optimization of application mapping is essential in the design of NoC. In this study, a greedy algorithm is utilized as the first technique to place the maximum communicating tasks together to give the main algorithm a head start. Then, a meta-heuristic Cuckoo Search via Levy flight is employed further to optimize the placement of tasks on the NoC cores. The greedy algorithm furnishes a relatively pre-processed base to the cuckoo search optimization (CSO), which eventually helps in the fast convergence of the main algorithm. The analysis of the results shows that the proposed algorithm outperformed the state-of-the-art techniques in NoC application mapping in terms of various performance metrics, such as communication cost, energy consumption, and average packet latency.
Keyword:
Task analysis
Topology
Sociology
Genetic algorithms
Costs
Computer architecture
Statistics
Application mapping
communication cost
cuckoo search
latency
Levy flight
network on chip
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
OPAIC: An optimization technique to improve energy consumption and performance in application specific network on chips.png)
MEASUREMENT
MEASUREMENTIF5.6
PREAI
分享收藏
查看更多内容