RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2021
- ISCA 2021
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19 results for Chia-Yu Chen
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
- Chi-Chun 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
Hybrid 8-bit floating point (HFP8) training and inference for deep neural networks
- Xiao Sun
- Jungwook Choi
- et al.
- 2019
- NeurIPS 2019
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
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