Deep Partitioned Training From Near-Storage Computing to DNN Accelerators. - Yongjoo Jang; Sejin Kim; Daehoon Kim; Sungjin Lee 001; Jaeha Kung (IEEE Comput. Archit. Lett., 2021)

SEMS: Scalable Embedding Memory System for Accelerating Embedding-Based DNNs. - Sejin Kim; Jungwoo Kim; Yongjoo Jang; Jaeha Kung; Sungjin Lee 001 (IEEE Comput. Archit. Lett., 2022)

All-rounder: A flexible DNN accelerator with diverse data format support. - Seock-Hwan Noh; Seungpyo Lee; Banseok Shin; Sehun Park; Yongjoo Jang; Jaeha Kung (CoRR, 2023)

All-Rounder: A Flexible AI Accelerator With Diverse Data Format Support and Morphable Structure for Multi-DNN Processing. - Seock-Hwan Noh; Seungpyo Lee; Banseok Shin; Sehun Park; Yongjoo Jang; Jaeha Kung (IEEE Trans. Very Large Scale Integr. Syst., 2025)