RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2021
- ISCA 2021
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21 results for Sunil Shukla
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
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
INVITED: Accelerator Design for Deep Learning Training: Extended Abstract: Invited
- Ankur Agrawal
- Chia-Yu Chen
- et al.
- 2017
- DAC 2017
A compiler and runtime for heterogeneous computing
- Joshua Auerbach
- David F. Bacon
- et al.
- 2012
- DAC 2012
And then there were none: A stall-free real-time garbage collector for reconfigurable hardware
- David F. Bacon
- Perry Cheng
- et al.
- 2012
- PLDI 2012
Virtualization of heterogeneous machines
- Joshua Auerbach
- David F. Bacon
- et al.
- 2011
- DAC 2011
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
A 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
A Scalable Multi-TeraOPS Deep Learning Processor Core for AI Trainina and Inference
- Bruce Fleischer
- Sunil Shukla
- et al.
- 2018
- VLSI Circuits 2018