Direct Gradient Calculation: Simple and Variation-Tolerant On-Chip Training Method for Neural Networks. - Hyungyo Kim; Joon Hwang; Dongseok Kwon; Jangsaeng Kim; Min-Kyu Park; Jiseong Im; Byung-Gook Park; Jong-Ho Lee 002 (Adv. Intell. Syst., 2021)

Boosting the Accuracy of SRAM-Based in-Memory Architectures Via Maximum Likelihood-Based Error Compensation Method. - Hyungyo Kim; Naresh R. Shanbhag (ICASSP, 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)

Exploiting Intel Advanced Matrix Extensions (AMX) for Large Language Model Inference. - Hyungyo Kim; Gaohan Ye; Nachuan Wang; Amir Yazdanbakhsh; Nam Sung Kim (IEEE Comput. Archit. Lett., 2024)

Enhancing the Accuracy of 6T SRAM-Based In-Memory Architecture via Maximum Likelihood Detection. - Hyungyo Kim; Naresh R. Shanbhag (IEEE Trans. Signal Process., 2024)

LIA: A Single-GPU LLM Inference Acceleration with Cooperative AMX-Enabled CPU-GPU Computation and CXL Offloading. - Hyungyo Kim; Nachuan Wang; Qirong Xia; Jinghan Huang 001; Amir Yazdanbakhsh; Nam Sung Kim (ISCA, 2025)

The New LLM Bottleneck: A Systems Perspective on Latent Attention and Mixture-of-Experts. - Sungmin Yun 001; Seonyong Park; Hwayong Nam; Younjoo Lee; Gunjun Lee; Kwanhee Kyung; Sangpyo Kim; Nam Sung Kim; Jongmin Kim 007; Hyungyo Kim; Juhwan Cho; Seungmin Baek; et al. (CoRR, 2025)