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[JSSC'24] Codes for CSNR estimation on paper A 818–4094 TOPS/W Capacitor-Reconfigured Analog CIM for Unified Acceleration of CNNs and Transformers

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Keio-CSG/AnalogCIM-CSNR-Sim

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AnalogCIM-CSNR-Sim

This repository contains Python scripts for simulating and analyzing Signal-to-Noise Ratio (SNR) in Analog Compute-In-Memory (CIM) architectures. The simulation focuses on quantization effects and noise in CIM operations, providing insights into the performance of these systems under various conditions.

Features

  • Simulation of ACIM calculation process with quantization and noise
  • Analysis of SQNR and CSNR under various conditions
  • Visualization of results for different ADC bit resolutions and noise levels
  • Replication of results from published research papers

Requirements

  • Python 3.x
  • NumPy
  • Matplotlib

Usage

  1. Clone the repository:

    git clone https://github.com/Keio-CSG/AnalogCIM-CSNR-Sim
    
  2. Navigate to the project directory:

    cd AnalogCIM-CSNR-Sim
    
  3. Run 'CIM_CSNR_simulation.ipynb'

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[JSSC'24] Codes for CSNR estimation on paper A 818–4094 TOPS/W Capacitor-Reconfigured Analog CIM for Unified Acceleration of CNNs and Transformers

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