Naigang Wang

Publications

• A Provably Effective Method for Pruning Experts in Fine-tuned Sparse Mixture-of-Experts

  • • Mohammed Nowaz Rabbani Chowdhury
    • Meng Wang
    • et al.
  • 2024
  • ICML 2024

  Conference paper

• Improved Techniques for Quantizing Deep Networks with Adaptive Bit-Widths

  • • Ximeng Sun
    • Rameswar Panda
    • et al.
  • 2024
  • WACV 2024

  Conference paper

• Deep Compression of Pre-trained Transformer Models

  • • Naigang Wang
    • Chi-Chun Liu
    • et al.
  • 2022
  • NeurIPS 2022

  Conference paper

• A 7-nm Four-Core Mixed-Precision AI Chip with 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling

  • • Sae Kyu Lee
    • Ankur Agrawal
    • et al.
  • 2021
  • IEEE JSSC

  Paper

• 4-bit quantization of LSTM-based speech recognition models

  • • Andrea Fasoli
    • Chia-Yu Chen
    • et al.
  • 2021
  • INTERSPEECH 2021

  Conference paper

• Hardware-Aware Neural Architecture Search: Survey and Taxonomy

  • • Hadjer Benmeziane
    • Kaoutar El Maghraoui
    • et al.
  • 2021
  • IJCAI 2021

  Survey paper

• RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference

  • • Swagath Venkataramani
    • Vijayalakshmi Srinivasan
    • et al.
  • 2021
  • ISCA 2021

  Conference paper

• A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware Throttling

  • • Ankur Agrawal
    • Saekyu Lee
    • et al.
  • 2021
  • ISSCC 2021

  Conference paper

• Ultra-Low Precision 4-bit Training of Deep Neural Networks

  • • Xiao Sun
    • Naigang Wang
    • et al.
  • 2020
  • NeurIPS 2020

  Conference paper

• ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training

  • • Chia-Yu Chen
    • Jiamin Ni
    • et al.
  • 2020
  • NeurIPS 2020

  Conference paper