DeltaTrack: Flow-Driven Multiple Object Tracking Accelerator with Variable LSB Approximation for Real-Time and Energy-Efficient Video Analytics
[paper]
Seunghyun Moon and Eunji Kwon
IEEE Transactions on Circuits and Systems II: Express Briefs (TCAS-II) 2025.
T-REX: Hardware-Software Co-Optimized Transformer Accelerator with Reduced External Memory Access and Enhanced Hardware Utilization
[paper]
Seunghyun Moon, Mao Li, Gregory K. Chen, Phil C. Knag, Ram K. Krishnamurthy and Mingoo Seok
IEEE Journal of Solid-State Circuits (JSSC) 2025.
Before 2025
Multipurpose Deep-Learning Accelerator for Arbitrary Quantization
with Reduction of Storage, Logic, and Latency Waste
[paper]
Seunghyun Moon, Han-Gyeol Mun, Hyunwoo Son and Jae-Yoon Sim
IEEE Journal of Solid-State Circuits (JSSC) 2024.
Bottleneck-Stationary Compact Model Accelerator with Reduced Requirement
on Memory Bandwidth for Edge Applications
[paper]
Han-Gyeol Mun, Seunghyun Moon, Byungjun Kim, Kyeong-Jun Lee and Jae-Yoon Sim
IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I) 2023.
A 384G Output NonZeros/J Graph Convolutional Neural Network Accelerator
[paper]
Kyeong-Jun Lee, Seunghyun Moon and Jae-Yoon Sim
IEEE Transactions on Circuits and Systems II: Express Briefs (TCAS-II) 2022.
An 8.9–71.3 TOPS/W Deep Learning Accelerator for Arbitrarily Quantized Neural Networks
[paper]
Seunghyun Moon, Kyeong-Jun Lee, Han-Gyeol Mun, Byungjun Kim and Jae-Yoon Sim
IEEE Transactions on Circuits and Systems II: Express Briefs (TCAS-II) 2022.