Hybrid 8-bit floating point (HFP8) training and inference for deep neural networks
- Xiao Sun
- Jungwook Choi
- et al.
- 2019
- NeurIPS 2019
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19 results for Chia-Yu Chen
Custom Sub-Systems and Circuits for Deep Learning: Guest Editorial Overview
- Chia-Yu Chen
- Boris Murmann
- et al.
- 2019
- IEEE JESTCS
Accumulation bit-width scaling for ultra-low precision training of deep networks
- Charbel Sakr
- Naigang Wang
- et al.
- 2019
- ICLR 2019
Training deep neural networks with 8-bit floating point numbers
- Naigang Wang
- Jungwook Choi
- et al.
- 2018
- NeurIPS 2018
A Scalable Multi-TeraOPS Core for AI Training and Inference
- Sunil Shukla
- Bruce Fleischer
- et al.
- 2018
- IEEE SSC-L
A Scalable Multi-TeraOPS Deep Learning Processor Core for AI Trainina and Inference
- Bruce Fleischer
- Sunil Shukla
- et al.
- 2018
- VLSI Circuits 2018
Exploiting approximate computing for deep learning acceleration
- Chia-Yu Chen
- Jungwook Choi
- et al.
- 2018
- DATE 2018
ADaComP: Adaptive residual gradient compression for data-parallel distributed training
- Chia-Yu Chen
- Jungwook Choi
- et al.
- 2018
- AAAI 2018
INVITED: Accelerator Design for Deep Learning Training: Extended Abstract: Invited
- Ankur Agrawal
- Chia-Yu Chen
- et al.
- 2017
- DAC 2017