A 7-nm Four-Core Mixed-Precision AI Chip with 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling
- Sae Kyu Lee
- Ankur Agrawal
- et al.
- 2021
- IEEE JSSC
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Publications
11 results for Xiao Sun
4-bit quantization of LSTM-based speech recognition models
- Andrea Fasoli
- Chia-Yu Chen
- et al.
- 2021
- INTERSPEECH 2021
Conference paperRaPiD: AI Accelerator for Ultra-Low Precision Training and Inference
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2021
- ISCA 2021
Conference paperA 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
Conference paperUltra-Low Precision 4-bit Training of Deep Neural Networks
- Xiao Sun
- Naigang Wang
- et al.
- 2020
- NeurIPS 2020
Conference paperScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
- Chia-Yu Chen
- Jiamin Ni
- et al.
- 2020
- NeurIPS 2020
Conference paperEfficient AI System Design with Cross-Layer Approximate Computing
- Swagath Venkataramani
- Xiao Sun
- et al.
- 2020
- Proceedings of the IEEE
PaperA 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
Conference paperHybrid 8-bit floating point (HFP8) training and inference for deep neural networks
- Xiao Sun
- Jungwook Choi
- et al.
- 2019
- NeurIPS 2019
Conference paperDLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference
- Ankur Agrawal
- Bruce Fleischer
- et al.
- 2019
- ARITH 2019
Conference paper