Swagath Venkataramani

Publications

• Deep Compression of Pre-trained Transformer Models

  • • Naigang Wang
    • Charlie Liu
    • et al.
  • 2022
  • NeurIPS 2022

• Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization

  • • Andrea Fasoli
    • Chia-Yu Chen
    • et al.
  • 2022
  • INTERSPEECH 2022

• Accelerating DNN Training Through Selective Localized Learning

  • • Sarada Krithivasan
    • Sanchari Sen
    • et al.
  • 2022
  • Frontiers in Neuroscience

• 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

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

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

• Efficacy of Pruning in Ultra-Low Precision DNNs

  • • Sanchari Sen
    • Swagath Venkataramani
    • et al.
  • 2021
  • ISLPED 2021

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

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

• Efficient Management of Scratch-Pad Memories in Deep Learning Accelerators

  • • Subhankar Pal
    • Swagath Venkataramani
    • et al.
  • 2021
  • ISPASS 2021

• 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

• Value Similarity Extensions for Approximate Computing in General-Purpose Processors

  • • Younghoon Kim
    • Swagath Venkataramani
    • et al.
  • 2021
  • DATE 2021