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Predictions optimal routing algorithm based on artificial intelligence technique for 3D NoC systems

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Abstract

Recently, the demand for features such as shrinkable sizes, and the concurrent need to pack increasing numbers of transistors into a single chip, have led to the utilization of hundreds of CMPs as processer elements for significant data processing, such as cloud computing systems with high performance and minimum latency-power consumption. A 3D NoC is introduced as a promising solution for the next generations of CMPs. However, there are different design issues, as selecting an efficient routing algorithm is a process which still faces some challenges. In this paper, to handle the deficiencies of the selection of the optimal routing algorithms, artificial intelligence technology is used to predict the efficient routing algorithm with higher throughput and lower power consumption. Experimental results based on the 3D NOXIM simulator are presented, and illustrate that the performance of the proposed system can predict, with high accuracy, optimal routing algorithms by switching between existing 3D routing algorithms, depending on the traffic load rate for the NoC system. The NN-prediction approach is tested under PARSEC workloads to validate the effectiveness of 3D NoC throughput, energy consumption and hotspot distribution metrics.

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  1. Department of Electrical and Computer Engineering, Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada

    Furat Al-Obaidy & Farah A. Mohammadi

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  1. Furat Al-Obaidy
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  2. Farah A. Mohammadi
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Correspondence to Furat Al-Obaidy.

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Al-Obaidy, F., Mohammadi, F.A. Predictions optimal routing algorithm based on artificial intelligence technique for 3D NoC systems. Microsyst Technol 27, 3313–3323 (2021). https://doi.org/10.1007/s00542-020-05084-1

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