Swagath Venkataramani

Publications

• MixTrain: accelerating DNN training via input mixing

  • • Sarada Krithivasan
    • Sanchari Sen
    • et al.
  • 2024
  • Frontiers in Artificial Intelligence

• A Software-Assisted Peak Current Regulation Scheme to Improve Power-Limited Inference Performance in a 5nm AI SoC

  • • Monodeep Kar
    • Joel Silberman
    • et al.
  • 2024
  • ISSCC 2024

• DNNDaSher: A Compiler Framework for Dataflow Compatible End-to-End Acceleration on IBM AIU

  • • Sanchari Sen
    • Shubham Jain
    • et al.
  • 2024
  • IEEE Micro

• Power-Limited Inference Performance Optimization Using a Software-Assisted Peak Current Regulation Scheme in a 5-nm AI SoC

  • • Monodeep Kar
    • Joel Silberman
    • et al.
  • 2024
  • IEEE Journal of Solid-State Circuits

• Deep Compression of Pre-trained Transformer Models

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

• Approximate computing and the efficient machine learning expedition

  • • Jörg Henkel
    • Hai Li
    • et al.
  • 2022
  • ICCAD 2022

• OnSRAM: Efficient Inter-Node On-Chip Scratchpad Management in Deep Learning Accelerators

  • • Subhankar Pal
    • Swagath Venkataramani
    • et al.
  • 2022
  • Transactions on Embedded Computing Systems

• 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