Publications

This is our catalog of recent publications authored by IBM researchers, in collaboration with the global research community. We’re currently adding our back catalog of more than 110,000 publications. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.

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30 results for Swagath Venkataramani

RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference
- - Swagath Venkataramani
  - Vijayalakshmi Srinivasan
  - et al.
- 2021
- ISCA 2021
Ultra-Low Precision 4-bit Training of Deep Neural Networks
- - Xiao Sun
  - Naigang Wang
  - et al.
- 2020
- NeurIPS 2020
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
- - Chia-Yu Chen
  - Jiamin Ni
  - et al.
- 2020
- NeurIPS 2020
Deep Compression of Pre-trained Transformer Models
- - Naigang Wang
  - Charlie Liu
  - et al.
- 2022
- NeurIPS 2022
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
A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and Inference
- - Jinwook Oh
  - Sae Kyu Lee
  - et al.
- 2020
- VLSI Circuits 2020
Hybrid 8-bit floating point (HFP8) training and inference for deep neural networks
- - Xiao Sun
  - Jungwook Choi
  - et al.
- 2019
- NeurIPS 2019
BiScaled-DNN: Quantizing long-tailed datastructures with two scale factors for deep neural networks
- - Shubham Jain
  - Swagath Venkataramani
  - et al.
- 2019
- DAC 2019
A Scalable Multi-TeraOPS Deep Learning Processor Core for AI Trainina and Inference
- - Bruce Fleischer
  - Sunil Shukla
  - et al.
- 2018
- VLSI Circuits 2018
DyHard-DNN: Even more DNN acceleration with dynamic hardware reconfiguration
- - Mateja Putic
  - Alper Buyuktosunoglu
  - et al.
- 2018
- DAC 2018