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)

Samsung PIM/PNM for Transfmer Based AI : Energy Efficiency on PIM/PNM Cluster. - Jin Hyun Kim; Yuhwan Ro; Jinin So; Sukhan Lee 002; Shinhaeng Kang; YeonGon Cho; Hyeonsu Kim; Byeongho Kim; Kyungsoo Kim 003; Sangsoo Park; Jin-Seong Kim; Sanghoon Cha; et al. (HCS, 2023)

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)

The Breakthrough Memory Solutions for Improved Performance on LLM Inference. - Byeongho Kim; Sanghoon Cha; Sangsoo Park; Jieun Lee; Sukhan Lee 002; Shinhaeng Kang; Jinin So; Kyungsoo Kim 003; Jin Jung; Jong-Geon Lee; Sunjung Lee; Yoonah Paik; et al. (IEEE Micro, 2024)

AiDE: Attention-FFN Disaggregated Execution for Cost-Effective LLM Decoding on CXL-PNM. - Kyungsoo Kim 003; Omin Kwon; Yeonhong Park; Jae W. Lee (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)