RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2021
- ISCA 2021
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59 results for Leland Chang
A Switched-Capacitor Integer Compute Unit with Decoupled Storage and Arithmetic for Cloud AI Inference in 5nm CMOS
- Ankur Agrawal
- Monodeep Kar
- et al.
- 2023
- VLSI Technology 2023
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
BiScaled-DNN: Quantizing long-tailed datastructures with two scale factors for deep neural networks
- Shubham Jain
- Swagath Venkataramani
- et al.
- 2019
- DAC 2019
System Performance: From Enterprise to AI
- Arvind Kumar
- Leland Chang
- et al.
- 2018
- IEDM 2018
Compensated-DNN: Energy efficient low-precision deep neural networks by compensating quantization errors
- Shubham Jain
- Swagath Venkataramani
- et al.
- 2018
- DAC 2018
Ultra-high-Q air-core slab inductors for on-chip power conversion
- Naigang Wang
- David Goren
- et al.
- 2014
- IEDM 2014
A 0.1pJ/b 5-to-10Gb/s charge-recycling stacked low-power I/O for on-chip signaling in 45nm CMOS SOI
- Yong Liu
- Ping-Hsuan Hsieh
- et al.
- 2013
- ISSCC 2013
Near-threshold operation for power-efficient computing? It depends...
- Leland Chang
- Wilfried Haensch
- 2012
- DAC 2012