| 2025 | ISCA | Debunking the CUDA Myth Towards GPU-based AI Systems: Evaluation of the Performance and Programmability of Intel's Gaudi NPU for AI Model Serving. | Yunjae Lee, Juntaek Lim, Jehyeon Bang, Eunyeong Cho, Huijong Jeong, Taesu Kim, Hyungjun Kim, Joonhyung Lee, Jinseop Im, Ranggi Hwang, Se Jung Kwon, Dongsoo Lee, Minsoo Rhu |
| 2024 | AAAI | OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models. | Changhun Lee, Jungyu Jin, Taesu Kim, Hyungjun Kim, Eunhyeok Park |
| 2024 | ICML | SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks. | Jiwon Song, Kyungseok Oh, Taesu Kim, Hyungjun Kim, Yulhwa Kim, Jae-Joon Kim |
| 2024 | Interspeech | RepTor: Re-parameterizable Temporal Convolution for Keyword Spotting via Differentiable Kernel Search. | Eunik Park, Daehyun Ahn, Hyungjun Kim |
| 2024 | ICSOC | LARE-HPA: Co-optimizing Latency and Resource Efficiency for Horizontal Pod Autoscaling in Kubernetes. | Donggyun Kim, Hyungjun Kim, EunYoung Lee, Heonchang Yu |
| 2024 | ICSOC | Optimizing Traffic Allocation for Multi-replica Microservice Deployments in Edge Cloud. | Hokun Park, Hyungjun Kim, Donggyun Kim, Gyujeong Lim, Heonchang Yu |
| 2023 | ICCV | INSTA-BNN: Binary Neural Network with INSTAnce-aware Threshold. | Changhun Lee, Hyungjun Kim, Eunhyeok Park, Jae-Joon Kim |
| 2023 | WACV | Searching for Robust Binary Neural Networks via Bimodal Parameter Perturbation. | Daehyun Ahn, Hyungjun Kim, Taesu Kim, Eunhyeok Park, Jae-Joon Kim |
| 2022 | DAC | TAIM: ternary activation in-memory computing hardware with 6T SRAM array. | Nameun Kang, Hyungjun Kim, Hyunmyung Oh, Jae-Joon Kim |
| 2021 | CVPR | Improving Accuracy of Binary Neural Networks Using Unbalanced Activation Distribution. | Hyungjun Kim, Jihoon Park, Changhun Lee, Jae-Joon Kim |
| 2021 | DATE | Mapping Binary ResNets on Computing-In-Memory Hardware with Low-bit ADCs. | Yulhwa Kim, Hyungjun Kim, Jihoon Park, Hyunmyung Oh, Jae-Joon Kim |
| 2020 | DAC | Algorithm/Hardware Co-Design for In-Memory Neural Network Computing with Minimal Peripheral Circuit Overhead. | Hyungjun Kim, Yulhwa Kim, Sungju Ryu, Jae-Joon Kim |
| 2020 | ICCAD | Energy-efficient XNOR-free In-Memory BNN Accelerator with Input Distribution Regularization. | Hyungjun Kim, Hyunmyung Oh, Jae-Joon Kim |
| 2020 | ICLR | BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations. | Hyungjun Kim, Kyungsu Kim, Jinseok Kim, Jae-Joon Kim |
| 2019 | ASPDAC | In-memory batch-normalization for resistive memory based binary neural network hardware. | Hyungjun Kim, Yulhwa Kim, Jae-Joon Kim |
| 2019 | DAC | BitBlade: Area and Energy-Efficient Precision-Scalable Neural Network Accelerator with Bitwise Summation. | Sungju Ryu, Hyungjun Kim, Wooseok Yi, Jae-Joon Kim |
| 2018 | ISLPED | Input-Splitting of Large Neural Networks for Power-Efficient Accelerator with Resistive Crossbar Memory Array. | Yulhwa Kim, Hyungjun Kim, Daehyun Ahn, Jae-Joon Kim |
| 2018 | SIGMOD | PREFER: PREdiction Model for Financial Entity Relation. | Hoyeop Lee, Jongseon Park, Hyungjun Kim, Hyunsouk Cho, Geonsoo Kim |
| 2013 | DAC | Dynamic voltage and frequency scaling for shared resources in multicore processor designs. | Xi Chen, Zheng Xu, Hyungjun Kim, Paul V. Gratz, Jiang Hu, Michael Kishinevsky, mit Y. Ogras, Raid Zuhair Ayoub |
| 2013 | ICCD | Power gating with block migration in chip-multiprocessor last-level caches. | David Kadjo, Hyungjun Kim, Paul Gratz, Jiang Hu, Raid Ayoub |
| 2013 | MICRO | Use it or lose it: wear-out and lifetime in future chip multiprocessors. | Hyungjun Kim, Arseniy Vitkovskiy, Paul V. Gratz, Vassos Soteriou |
| 2011 | IGARSS | Toward global-scale data assimilation using SWOT: Requirements for global hydrodynamics models. | Dai Yamazaki, Douglas E. Alsdorf, Hyungjun Kim, Shinjiro Kanae, Taikan Oki, Konstantinos Andreadis |