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Posts by Collection
portfolio
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publications
C FIXAR: A Fixed-Point Deep Reinforcement Learning Platform with Quantization-Aware Training and Adaptive Parallelism [paper]
ACM/IEEE Design Automation Conference (DAC), 2021
Je Yang, Seongmin Hong, and Joo-Young Kim
C LearningGroup: A Real-Time Sparse Training on FPGA via Learnable Weight Grouping for Multi-Agent Reinforcement Learning [paper]
IEEE International Conference on Field Programmable Technology (ICFPT), 2022
Je Yang, JaeUk Kim, and Joo-Young Kim
C JNPU: A 1.04TFLOPS Joint-DNN Training Processor with Speculative Quantization and Triple Heterogeneity on Microarchitecture / Precision / Dataflow [paper]
IEEE European Solid-State Circuits Conference (ESSCIRC), 2023
Je Yang, Sukbin Lim, Sukjin Lee, Jae-Young Kim, and Joo-Young Kim
C ReconFormer: A Multi-Level Run-time Reconfigurable System-on-Chip for Accelerating Transformers [paper]
IEEE International Conference on Field-Programmable Logic and Applications (FPL), 2025
Je Yang, Gabriele Tombesi, Joseph Zuckerman, and Luca P. Carloni
talks
Design- and Run-time Reconfigurable System-on-chip for Language Model Inference on Edge [paper]
Published:
Je Yang, Gabriele Tombesi, Joseph Zuckerman, and Luca P. Carloni
An Open-Source DNN Acceleration Fabric with Flexible Inter-Layer Pipelining Support
Published:
Gabriele Tombesi, Joseph Zuckerman, Je Yang, William Baisi, Kevin Lee, Davide Giri, and Luca P. Carloni
A Cache Coherence-Aware Runtime Reconfigurable System-on-Chip for Efficient Language Model Inference
Published:
Je Yang, Gracen Wallace, Joseph Zuckerman, Gabriele Tombesi, and Luca P. Carloni
teaching
CSEE4868 System-on-Chip Platforms
Fall 2024, Fall 2025
CSEE6868 Embedded Scalable Platforms
Spring 2025, Spring 2026
EE303 Digital System Design
Spring 2021, Fall 2022
EE488 Hardware Acceleration for Machine Learning
Spring 2022