Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In modern System-on-Chip (SoC) architectures, Networks-on-Chip (NoC) have emerged as the dominant interconnect solution for multi-core systems. However, conventional routing algorithms often fail to adapt dynamically to real-time traffic patterns and congestion, leading to increased latency and power consumption. This paper proposes a novel deep learning-based intelligent routing framework that leverages Deep Reinforcement Learning (DRL) to optimize routing decisions dynamically in NoC-based SoCs. The model is trained on synthetic and benchmark traffic patterns to learn adaptive policies that minimize latency and improve throughput. The proposed system integrates deep Q-learning agents into each router node, which collectively learn optimal paths based on local and global congestion states. Simulation results on 2D mesh and torus topologies using BookSim2 and SystemC demonstrate up to 30% latency reduction and 15% energy efficiency gains compared to traditional XY and odd-even algorithms.
"Intelligent Routing Algorithms for NoC-Based SoC Using Deep Learning", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 7, page no.a230-a233, July-2025, Available :http://www.ijrti.org/papers/IJRTI2507028.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator