Publications

This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. 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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56 results for Kailash Gopalakrishnan

4-bit quantization of LSTM-based speech recognition models
- - Andrea Fasoli
  - Chia-Yu Chen
  - et al.
- 2021
- INTERSPEECH 2021
Efficient Management of Scratch-Pad Memories in Deep Learning Accelerators
- - Subhankar Pal
  - Swagath Venkataramani
  - et al.
- 2021
- ISPASS 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
Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems
- - Swagath Venkataramani
  - Vijayalakshmi Srinivasan
  - et al.
- 2019
- HiPC 2019
Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators∗
- - Swagath Venkataramani
  - Jungwook Choi
  - et al.
- 2019
- IISWC 2019
DLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference
- - Ankur Agrawal
  - Bruce Fleischer
  - et al.
- 2019
- ARITH 2019
A Compiler for Deep Neural Network Accelerators to Generate Optimized Code for a Wide Range of Data Parameters from a Hand-crafted Computation Kernel
- - Eri Ogawa
  - Kazuaki Ishizaki
  - et al.
- 2019
- COOL CHIPS 2019
A Scalable Multi-TeraOPS Deep Learning Processor Core for AI Trainina and Inference
- - Bruce Fleischer
  - Sunil Shukla
  - et al.
- 2018
- VLSI Circuits 2018
True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization
- - Charbel Sakr
  - Jungwook Choi
  - et al.
- 2018
- ICASSP 2018
Exploiting approximate computing for deep learning acceleration
- - Chia-Yu Chen
  - Jungwook Choi
  - et al.
- 2018
- DATE 2018