Abstract
A network-on-chip (NoC) offers high performance, flexibility and scalability in communication infrastructure within multi-core platforms. However, NoCs contribute significantly to the overall system’s power consumption. The double-layer energy efficient synchronous-asynchronous circuit-switched NoC (CS-NoC) is proposed to enhance the power utilization. To reduce the dynamic power consumption, single-rail asynchronous protocols are utilized. The two-phase and four-phase encoding algorithms are analyzed to determine the most efficient technique. For the data layer, the two asynchronous protocols reduced the power consumption by 80%, with an increase in latency when compared with the fully synchronous protocol. However, the two-phase single-rail protocol had better performance compared with the four-phase protocol by 38%, with the same power consumption and a slight increase in area of 5%. Based on this conducted analysis, the asynchronous two-phase layer had significant power reduction yet operated at a moderate frequency. Therefore, the proposed NoC is divided into two data transfer layers with a single control layer. The data transfer layers are designed using synchronous and asynchronous protocols. The synchronous layer is designated to high-frequency loads, and the asynchronous layer is confined to low-frequency loads. The switching between the layers creates a trade-off between the maximum allowed frequency and the power consumption. The proposed NoC reduces the overall power consumption by 23% when compared with recent previous work. The NoC maintains the same system performance with an 8% area increase over the fully synchronous double-layer in the literature.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering
Cited by
2 articles.
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1. Granular Transistor-Level Approaches for QDI Asynchronous Crossbar Switches;2023 IEEE 66th International Midwest Symposium on Circuits and Systems (MWSCAS);2023-08-06
2. Efficient Transistor-Level QDI Asynchronous Switch for Neuromorphic Systems;2023 21st IEEE Interregional NEWCAS Conference (NEWCAS);2023-06-26