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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29 results for Jungwook Choi
RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2021
- ISCA 2021
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
Efficient AI System Design with Cross-Layer Approximate Computing
- Swagath Venkataramani
- Xiao Sun
- et al.
- 2020
- Proceedings of the IEEE
Hardware and Software Co-optimization for the Initialization Failure of the ReRAM-based Cross-bar Array
- Youngseok Kim
- S. Kim
- et al.
- 2020
- ACM JETC
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
Hybrid 8-bit floating point (HFP8) training and inference for deep neural networks
- Xiao Sun
- Jungwook Choi
- et al.
- 2019
- NeurIPS 2019
Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2019
- HiPC 2019
Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators∗
- Swagath Venkataramani
- Jungwook Choi
- et al.
- 2019
- IISWC 2019
DeepTools: Compiler and Execution Runtime Extensions for RaPiD AI Accelerator
- Swagath Venkataramani
- Jungwook Choi
- et al.
- 2019
- IEEE Micro