Research Groups

대규모 회로 및 시스템 연구실


Prof. : Prof. KIM JAE-JOON

Research Area : VLSI

  • About the Laboratory & Research Area
  • We design energy-efficient and high-performance deep learning hardware accelerators. We focus on making neural networks lighter to enable deep learning computation in energy-constrained embedded computing devices. We also invent various circuits with low-power and variation-aware characteristics.
  • Research Interests & Projects
  • Our main/current interests are

    A. Neural Network-Friendly Hardware / Hardware-Friendly Neural Network
    - Network Compression: Pruning, Quantization
    - Efficient Sparse Matrix Handling in NN Hardware
    - Variable-Precision Neural Network Hardware
    - Multi-bit Neural Network with Bitwise Activation

    B. Near-/In-Memory Neural Network Computing
    - Resistive Memory Based Neural Network Hardware
    - SRAM based Binary Neural Network Hardware
    - Mapping Large Neural Network on Memory Arrays
    - Minimizing the Overhead of Peripheral Circuits(ADC/DAC) for In-Memory DNN Computing
    - Process-Variation tolerant In-Memory NN Computing
    - Near-Memory NN Processing in 3D High Bandwidth Memory (HBM)
    - Spin Device based Neural Network Hardware
  • Journals & Patents
  • http://vlsi.snu.ac.kr/publications/