Kailash Gopalakrishnan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
15
Venues
12
Active years
2015–2022
Best venue rank
A*
Where they publish
Papers
15 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2022 | Interspeech | Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization. | Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Kailash Gopalakrishnan |
| 2021 | Interspeech | 4-Bit Quantization of LSTM-Based Speech Recognition Models. | Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltn Tske, Kailash Gopalakrishnan |
| 2021 | ISCA | RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun, Naigang Wang, Chia-Yu Chen, Allison Allain, James Bonanno, Nianzheng Cao, Robert Casatuta, Matthew Cohen, Bruce M. Fleischer, Michael Guillorn, Howard Haynie, Jinwook Jung, Mingu Kang, Kyu-Hyoun Kim, Siyu Koswatta, Sae Kyu Lee, Martin Lutz, Silvia M. Mueller, Jinwook Oh, Ashish Ranjan, Zhibin Ren, Scot Rider, Kerstin Schelm, Michael Scheuermann, Joel Silberman, Jie Yang, Vidhi Zalani, Xin Zhang, Ching Zhou, Matthew M. Ziegler, Vinay Shah, Moriyoshi Ohara, Pong-Fei Lu, Brian W. Curran, Sunil Shukla, Leland Chang, Kailash Gopalakrishnan |
| 2021 | ISPASS | Efficient Management of Scratch-Pad Memories in Deep Learning Accelerators. | Subhankar Pal, Swagath Venkataramani, Viji Srinivasan, Kailash Gopalakrishnan |
| 2019 | ARITH | DLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference. | Ankur Agrawal, Bruce M. Fleischer, Silvia M. Mueller, Xiao Sun, Naigang Wang, Jungwook Choi, Kailash Gopalakrishnan |
| 2019 | DAC | BiScaled-DNN: Quantizing Long-tailed Datastructures with Two Scale Factors for Deep Neural Networks. | Shubham Jain, Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang |
| 2019 | HiPC | Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Philip Heidelberger, Leland Chang, Kailash Gopalakrishnan |
| 2019 | ICLR | Accumulation Bit-Width Scaling For Ultra-Low Precision Training Of Deep Networks. | Charbel Sakr, Naigang Wang, Chia-Yu Chen, Jungwook Choi, Ankur Agrawal, Naresh R. Shanbhag, Kailash Gopalakrishnan |
| 2018 | AAAI | AdaComp : Adaptive Residual Gradient Compression for Data-Parallel Distributed Training. | Chia-Yu Chen, Jungwook Choi, Daniel Brand, Ankur Agrawal, Wei Zhang, Kailash Gopalakrishnan |
| 2018 | DATE | Exploiting approximate computing for deep learning acceleration. | Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Viji Srinivasan, Swagath Venkataramani |
| 2018 | ICASSP | True Gradient-Based Training of Deep Binary Activated Neural Networks Via Continuous Binarization. | Charbel Sakr, Jungwook Choi, Zhuo Wang, Kailash Gopalakrishnan, Naresh R. Shanbhag |
| 2018 | ISLPED | Across the Stack Opportunities for Deep Learning Acceleration. | Vijayalakshmi Srinivasan, Bruce M. Fleischer, Sunil Shukla, Matthew M. Ziegler, Joel Silberman, Jinwook Oh, Jungwook Choi, Silvia M. Mueller, Ankur Agrawal, Tina Babinsky, Nianzheng Cao, Chia-Yu Chen, Pierce Chuang, Thomas W. Fox, George Gristede, Michael Guillorn, Howard Haynie, Michael J. Klaiber, Dongsoo Lee, Shih-Hsien Lo, Gary W. Maier, Michael Scheuermann, Swagath Venkataramani, Christos Vezyrtzis, Naigang Wang, Fanchieh Yee, Ching Zhou, Pong-Fei Lu, Brian W. Curran, Leland Chang, Kailash Gopalakrishnan |
| 2018 | ISLPED | Taming the beast: Programming Peta-FLOP class Deep Learning Systems. | Swagath Venkataramani, Vijayalakshmi Srinivasan, Jungwook Choi, Kailash Gopalakrishnan, Leland Chang |
| 2017 | DAC | Accelerator Design for Deep Learning Training: Extended Abstract: Invited. | Ankur Agrawal, Chia-Yu Chen, Jungwook Choi, Kailash Gopalakrishnan, Jinwook Oh, Sunil Shukla, Viji Srinivasan, Swagath Venkataramani, Wei Zhang |
| 2015 | ICML | Deep Learning with Limited Numerical Precision. | Suyog Gupta, Ankur Agrawal, Kailash Gopalakrishnan, Pritish Narayanan |