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Deep Reinforcement Learning to Dynamically Configure NoC Resources

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New research paper titled “Deep Reinforcement Learning Enabled Self-Configurable Networks-on-Chip for High-Performance and Energy-Efficient Computing Systems” from Md Farhadur Reza at Eastern Illinois University.

Find the open access technical paper here. Published June 2022.

M. F. Reza, “Deep Reinforcement Learning Enabled Self-Configurable Networks-on-Chip for High-Performance and Energy-Efficient Computing Systems,” in EEE Access, 2022, doi: 10.1109/ACCESS.2022.3182500.

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Further Reading:
Optimizing NoC-Based Designs
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There are at least three architectural layers to processor design, each of which plays a significant role.
AI-Based Method To Prune The Design Space Of Heterogeneous NoCs
Researchers propose “an approach based on generative AI to help pruning complex design spaces for heterogeneous NoCs, according to configurable performance objectives.”



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