IEICE Transactions on Information and Systems
Online ISSN : 1745-1361
Print ISSN : 0916-8532
Regular Section
6T-8T Hybrid SRAM for Lower-Power Neural-Network Processing by Lowering Operating Voltage
Ji WURuoxi YUKazuteru NAMBA
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2024 Volume E107.D Issue 9 Pages 1278-1280

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Abstract

This letter introduces an innovation for the heterogeneous storage architecture of AI chips, specifically focusing on the integration of six transistors(6T) and eight transistors(8T) hybrid SRAM. Traditional approaches to reducing SRAM power consumption typically involve lowering the operating voltage, a method that often substantially diminishes the recognition rate of neural networks. However, the innovative design detailed in this letter amalgamates the strengths of both SRAM types. It operates at a voltage lower than conventional SRAM, thereby significantly reducing the power consumption in neural networks without compromising performance.

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© 2024 The Institute of Electronics, Information and Communication Engineers
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