Restructuring Batch Normalization to Accelerate CNN Training. - Wonkyung Jung; Daejin Jung; Byeongho Kim; Sunjung Lee; Wonjong Rhee; Jung Ho Ahn (SysML, 2019)

MViD: Sparse Matrix-Vector Multiplication in Mobile DRAM for Accelerating Recurrent Neural Networks. - Byeongho Kim; Jongwook Chung; Eojin Lee; Wonkyung Jung; Sunjung Lee; Jaewan Choi; Jaehyun Park 006; Minbok Wi; Sukhan Lee 002; Jung Ho Ahn (IEEE Trans. Computers, 2020)

TRiM: Enhancing Processor-Memory Interfaces with Scalable Tensor Reduction in Memory. - Jaehyun Park 006; Byeongho Kim; Sungmin Yun 001; Eojin Lee; Minsoo Rhu; Jung Ho Ahn (MICRO, 2021)

TRiM: Tensor Reduction in Memory. - Byeongho Kim; Jaehyun Park 006; Eojin Lee; Minsoo Rhu; Jung Ho Ahn (IEEE Comput. Archit. Lett., 2021)

An Architecture of Sparse Length Sum Accelerator in AxDIMM. - Shinhaeng Kang; Byeongho Kim; Sukhan Lee 002; Kyomin Sohn (AICAS, 2022)

An FPGA-based RNN-T Inference Accelerator with PIM-HBM. - Shinhaeng Kang; Sukhan Lee 002; Byeongho Kim; Hweesoo Kim; Kyomin Sohn; Nam Sung Kim; Eojin Lee (FPGA, 2022)

Accelerating Transformer Networks through Recomposing Softmax Layers. - Jaewan Choi; Hailong Li; Byeongho Kim; Seunghwan Hwang; Jung Ho Ahn (IISWC, 2022)

GraNDe: Near-Data Processing Architecture With Adaptive Matrix Mapping for Graph Convolutional Networks. - Sungmin Yun 001; Byeongho Kim; Jaehyun Park 006; Hwayong Nam; Jung Ho Ahn; Eojin Lee (IEEE Comput. Archit. Lett., 2022)

MVP: An Efficient CNN Accelerator with Matrix, Vector, and Processing-Near-Memory Units. - Sunjung Lee; Jaewan Choi; Wonkyung Jung; Byeongho Kim; Jaehyun Park 006; Hweesoo Kim; Jung Ho Ahn (ACM Trans. Design Autom. Electr. Syst., 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)

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)

Duplex: A Device for Large Language Models with Mixture of Experts, Grouped Query Attention, and Continuous Batching. - Sungmin Yun 001; Kwanhee Kyung; Juhwan Cho; Jaewan Choi; Jongmin Kim 007; Byeongho Kim; Sukhan Lee 002; Kyomin Sohn; Jung Ho Ahn (MICRO, 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)

GraNDe: Efficient Near-Data Processing Architecture for Graph Neural Networks. - Sungmin Yun 001; Hwayong Nam; Jaehyun Park 006; Byeongho Kim; Jung Ho Ahn; Eojin Lee (IEEE Trans. Computers, 2024)

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)