The search functionality is under construction.
The search functionality is under construction.

Author Search Result

[Author] Ruoxi YU(1hit)

1-1hit
  • 6T-8T Hybrid SRAM for Lower-Power Neural-Network Processing by Lowering Operating Voltage Open Access

    Ji WU  Ruoxi YU  Kazuteru NAMBA  

     
    LETTER-Computer System

      Pubricized:
    2024/05/20
      Vol:
    E107-D No:9
      Page(s):
    1278-1280

    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.