RaPiD: AI Accelerator for Ultra-Low Precision Training and Inference
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2021
- ISCA 2021
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13 results for Mingu Kang
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
PROMISE: An end-to-End design of a programmable mixed-Signal accelerator for Machine-Learning algorithms
- Prakalp Srivastava
- Mingu Kang
- et al.
- 2018
- ISCA 2018
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 variation-tolerant in-memory machine learning classifier via on-chip training
- Sujan Gonugondla
- Mingu Kang
- et al.
- 2018
- 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
An MRAM-based deep in-memory architecture for deep neural networks
- Ameya D. Patil
- Haocheng Hua
- et al.
- 2019
- ISCAS 2019
Efficient AI System Design with Cross-Layer Approximate Computing
- Swagath Venkataramani
- Xiao Sun
- et al.
- 2020
- Proceedings of the IEEE
Deep In-Memory Architectures for Machine Learning-Accuracy Versus Efficiency Trade-Offs
- Mingu Kang
- Yongjune Kim
- et al.
- 2020
- IEEE TCAS-I