Z-PIM: A Sparsity-Aware Processing-in-Memory Architecture With Fully Variable Weight Bit-Precision for Energy-Efficient Deep Neural Networks. - Ji-Hoon Kim 004; Juhyoung Lee; Jinsu Lee; Jaehoon Heo; Joo-Young Kim 001 (IEEE J. Solid State Circuits, 2021)

T-PIM: A 2.21-to-161.08TOPS/W Processing-In-Memory Accelerator for End-to-End On-Device Training. - Jaehoon Heo; Junsoo Kim 002; Wontak Han; Sukbin Lim; Joo-Young Kim 001 (CICC, 2022)

Design of Processing-in-Memory With Triple Computational Path and Sparsity Handling for Energy-Efficient DNN Training. - Wontak Han; Jaehoon Heo; Junsoo Kim 002; Sukbin Lim; Joo-Young Kim 001 (IEEE J. Emerg. Sel. Topics Circuits Syst., 2022)

PRIMO: A Full-Stack Processing-in-DRAM Emulation Framework for Machine Learning Workloads. - Jaehoon Heo; Yongwon Shin; Sangjin Choi; Sungwoong Yune; Jung-Hoon Kim; Hyojin Sung; Youngjin Kwon; Joo-Young Kim 001 (ICCAD, 2023)

SP-PIM: A 22.41TFLOPS/W, 8.81Epochs/Sec Super-Pipelined Processing-In-Memory Accelerator with Local Error Prediction for On-Device Learning. - Jung-Hoon Kim; Jaehoon Heo; Wontak Han; Jaeuk Kim; Joo-Young Kim 001 (VLSI Technology and Circuits, 2023)

T-PIM: An Energy-Efficient Processing-in-Memory Accelerator for End-to-End On-Device Training. - Jaehoon Heo; Junsoo Kim 002; Sukbin Lim; Wontak Han; Joo-Young Kim 001 (IEEE J. Solid State Circuits, 2023)

A 38.5TOPS/W Point Cloud Neural Network Processor with Virtual Pillar and Quadtree-based Workload Management for Real-Time Outdoor BEV Detection. - Sukbin Lim; Jaehoon Heo; Jinho Yang; Joo-Young Kim 001 (CICC, 2024)

APINT: A Full-Stack Framework for Acceleration of Privacy-Preserving Inference of Transformers based on Garbled Circuits. - Hyunjun Cho; Jaeho Jeon; Jaehoon Heo; Joo-Young Kim 001 (ICCAD, 2024)

BLESS: Bandwidth and Locality Enhanced SMEM Seeding Acceleration for DNA Sequencing. - Seunghee Han; Seungjae Moon; Teokkyu Suh; Jaehoon Heo; Joo-Young Kim 001 (ISCA, 2024)

SP-PIM: A Super-Pipelined Processing-In-Memory Accelerator With Local Error Prediction for Area/Energy-Efficient On-Device Learning. - Jaehoon Heo; Jung-Hoon Kim; Wontak Han; Jaeuk Kim; Joo-Young Kim 001 (IEEE J. Solid State Circuits, 2024)

EXION: Exploiting Inter-and Intra-Iteration Output Sparsity for Diffusion Models. - Jaehoon Heo; Adiwena Putra; Jieon Yoon; Sungwoong Yune; Hangyeol Lee; Ji-Hoon Kim 004; Joo-Young Kim 001 (HPCA, 2025)

23.10 HuMoniX: A 57.3fps 12.8TFLOPS/W Text-to-Motion Processor with Inter-Iteration Output Sparsity and Inter-Frame Joint Similarity. - Jaehoon Heo; Adiwena Putra; Sungwoong Yune; Jieon Yoon; Hangyeol Lee; Jihoon Kim; Joo-Young Kim 001 (ISSCC, 2025)

Hawkeye: A Point Cloud Neural Network Processor With Virtual Pillar and Quadtree-Based Workload Management for Real-Time Outdoor BEV Detection. - Sukbin Lim; Jaehoon Heo; Jinho Yang; Joo-Young Kim 001 (IEEE J. Solid State Circuits, 2025)