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This paper presents a self-adaptive 12T SRAM cell designed to enhance read stability and reliability for multi-core processing elements, particularly in machine learning applications. The proposed SRAM architecture incorporates positive feedback and selective word lines to improve performance while reducing power dissipation by 12% compared to existing designs. The study highlights the importance of stability and low power in SRAM cells for efficient computation in convolutional neural networks.

Author

vaishnavtinku200310

Language

EN