Understanding and Reducing Weight-Load Overhead of Systolic Deep Learning Accelerators. - Jinwon Joo; Minyong Yoon; Jungwook Choi; Mingu Kang; Jong-Geon Lee; Jinin So; IlKwon Yun; Yongsuk Kwon; KyungSoo Kim 003 (ISOCC, 2021)

Near-Memory Processing in Action: Accelerating Personalized Recommendation With AxDIMM. - Liu Ke 001; Xuan Zhang 001; Jinin So; Jong-Geon Lee; Shinhaeng Kang; Sukhan Lee 002; Songyi Han; YeonGon Cho; Jin Hyun Kim; Yongsuk Kwon; KyungSoo Kim 003; Jin Jung; et al. (IEEE Micro, 2022)

A Hardware-Friendly Tiled Singular-Value Decomposition-Based Matrix Multiplication for Transformer-Based Models. - Hailong Li; Jaewan Choi; Yongsuk Kwon; Jung Ho Ahn (IEEE Comput. Archit. Lett., 2023)

AttAcc! Unleashing the Power of PIM for Batched Transformer-based Generative Model Inference. - Jaehyun Park 006; Jaewan Choi; Kwanhee Kyung; Michael Jaemin Kim; Yongsuk Kwon; Nam Sung Kim; Jung Ho Ahn (ASPLOS (2), 2024)

An LPDDR-based CXL-PNM Platform for TCO-efficient Inference of Transformer-based Large Language Models. - Sangsoo Park; KyungSoo Kim 003; Jinin So; Jin Jung; Jonggeon Lee; Kyoungwan Woo; Nayeon Kim 006; Younghyun Lee; Hyungyo Kim; Yongsuk Kwon; Jinhyun Kim; Jieun Lee; et al. (HPCA, 2024)

CLAY: CXL-based Scalable NDP Architecture Accelerating Embedding Layers. - Sungmin Yun 001; Hwayong Nam; Kwanhee Kyung; Jaehyun Park 006; Byeongho Kim; Yongsuk Kwon; Eojin Lee; Jung Ho Ahn (ICS, 2024)

Cosmos: A CXL-Based Full In-Memory System for Approximate Nearest Neighbor Search. - Seoyoung Ko; Hyunjeong Shim; Wanju Doh; Sungmin Yun 001; Jinin So; Yongsuk Kwon; Sang-Soo Park; Si-Dong Roh; Minyong Yoon; Taeksang Song; Jung Ho Ahn (IEEE Comput. Archit. Lett., 2025)

Accelerating Confidential Recommendation Model Inference With Near-Memory Processing. - Wenjie Xiong 001; Liu Ke 001; Maxim Ostapenko; Yongmin Tai; Yeongon Cho; Joon-Ho Song; Jinin So; Kyungsoo Kim 003; Yongsuk Kwon; Jin Jung; Jieun Lee; Byeongho Kim; et al. (IEEE Trans. Dependable Secur. Comput., 2025)