| 2026 | CGO | Flow-Graph-Aware Tiling and Rescheduling for Memory-Efficient On-Device Inference. | Yeonoh Jeong, Taehyeong Park, Yongjun Park |
| 2026 | EuroSys | FlexiQ: Adaptive Mixed-Precision Quantization for Latency/Accuracy Trade-Offs in Deep Neural Networks. | Jaemin Kim, Hongjun Um, Sungkyun Kim, Yongjun Park, Jiwon Seo |
| 2026 | ICDE | Efficient Data Processing using On-the-Fly Host-PIM Interactions in a Commodity PIM System. | Hyojune Kim, Jeonghyeon Joo, Taehyeong Park, Yongjun Park, Hyuck Han, Sooyong Kang |
| 2026 | ICS | Three Birds, One Stone: Fast, Accurate-aware and Cost-Efficient Accelerator for Ternary LLM. | Wonseok Jung, Junseok Kang, Sangwon Shin, Hongjun Um, Jangho Lim, Yongjun Park, Gunjae Koo, Sangwoo Park, Taeweon Suh |
| 2026 | ISPASS | Compiler and System Optimizations for Gem5 Simulator. | Haneul Park, Siddharth Agarwal, Pradyun Narkadamilli, Kiung Jung, Yongjun Park, Ipoom Jeong, Nam Sung Kim |
| 2025 | CGO | Accelerating LLMs using an Efficient GEMM Library and Target-Aware Optimizations on Real-World PIM Devices. | Hyeoncheol Kim, Taehoon Kim, Taehyeong Park, Donghyeon Kim, Yongseung Yu, Hanjun Kim, Yongjun Park |
| 2025 | CGO | CUrator: An Efficient LLM Execution Engine with Optimized Integration of CUDA Libraries. | Yoon Noh Lee, Yongseung Yu, Yongjun Park |
| 2025 | CIKM | An Efficient PIM-Based Graph Engine on a Single Machine. | Myung-Hwan Jang, Min-Kyeong Shin, Taehyeong Park, Yongjun Park, Sang-Wook Kim |
| 2025 | DAC | Supporting Register-based Addressing Modes for in-DRAM PIM ISAs. | Seok Young Kim, Byung Ho Choi, Seokwon Kang, Yongjun Park, Seon Wook Kim |
| 2025 | ICS | PIM-CARE: A Compiler-Assisted Dynamic Resource Allocation Framework for Real-world DRAM PIM. | Inyong Hwang, Donghyeon Kim, Seokwon Kang, Taehyeong Park, Taehoon Kim, Jiwon Seo, Hanjun Kim, Youngsok Kim, Yongjun Park |
| 2025 | ICS | SortingHat: System Topology-aware Scheduling of Deep Neural Network Models on Multi-GPU Systems. | Seok Namkoong, Taehyeong Park, Kiung Jung, Jinyoung Kim, Yongjun Park |
| 2025 | MICRO | PIM-CCA: An Efficient PIM Architecture with Optimized Integration of Configurable Functional Units. | Jeehyun Kim, Donghyeon Kim, Seokwon Kang, Bongjoon Hyun, Inho Lee, Yongjun Park |
| 2025 | WACV | Causal Representation-Based Domain Generalization on Gaze Estimation. | Younghan Kim, Kangryun Moon, Yongjun Park, Yonggyu Kim |
| 2024 | DATE | Discovering Efficient Fused Layer Configurations for Executing Multi-Workloads on Multi-Core NPUs. | Younghyun Lee, Hyejun Kim, Yongseung Yu, Myeongjin Cho, Jiwon Seo, Yongjun Park |
| 2023 | CIKM | SAGE: A Storage-Based Approach for Scalable and Efficient Sparse Generalized Matrix-Matrix Multiplication. | Myung-Hwan Jang, Yun-Yong Ko, Hyuck-Moo Gwon, Ikhyeon Jo, Yongjun Park, Sang-Wook Kim |
| 2023 | DATE | Block Group Scheduling: A General Precision-scalable NPU Scheduling Technique with Capacity-aware Memory Allocation. | Seokho Lee, Younghyun Lee, Hyejun Kim, Taehoon Kim, Yongjun Park |
| 2023 | ICCD | Tailoring CUTLASS GEMM using Supervised Learning. | Yongseung Yu, Donghyun Son, Younghyun Lee, Sunghyun Park, Giha Ryu, Myeongjin Cho, Jiwon Seo, Yongjun Park |
| 2023 | ICDE | Orchestrating Large-Scale SpGEMMs using Dynamic Block Distribution and Data Transfer Minimization on Heterogeneous Systems. | Taehyeong Park, Seokwon Kang, Myung-Hwan Jang, Sang-Wook Kim, Yongjun Park |
| 2022 | BMVC | Unified Negative Pair Generation toward Well-discriminative Feature Space for Face Recognition. | Junuk Jung, Seonhoon Lee, Heung-Seon Oh, Yongjun Park, Sungbin Son, Joochan Park |
| 2022 | CGO | SRTuner: Effective Compiler Optimization Customization by Exposing Synergistic Relations. | Sunghyun Park, Salar Latifi, Yongjun Park, Armand Behroozi, Byungsoo Jeon, Scott A. Mahlke |
| 2022 | MICRO | Networked SSD: Flash Memory Interconnection Network for High-Bandwidth SSD. | Jiho Kim, Seokwon Kang, Yongjun Park, John Kim |
| 2021 | ICCD | Legion: Tailoring Grouped Neural Execution Considering Heterogeneity on Multiple Edge Devices. | Kyunghwan Choi, Seongju Lee, Beom Woo Kang, Yongjun Park |
| 2021 | ICDM | MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems. | Yun-Yong Ko, Jae-Seo Yu, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, Sang-Wook Kim |
| 2020 | CGO | PreScaler: an efficient system-aware precision scaling framework on heterogeneous systems. | Seokwon Kang, Kyunghwan Choi, Yongjun Park |
| 2020 | DAC | Navigator: Dynamic Multi-kernel Scheduling to Improve GPU Performance. | Jiho Kim, John Kim, Yongjun Park |
| 2020 | DAC | Convergence-Aware Neural Network Training. | Hyungjun Oh, Yongseung Yu, Giha Ryu, Gunjoo Ahn, Yuri Jeong, Yongjun Park, Jiwon Seo |
| 2020 | ICDE | Optimization of GPU-based Sparse Matrix Multiplication for Large Sparse Networks. | Jeongmyung Lee, Seokwon Kang, Yongseung Yu, Yong-Yeon Jo, Sang-Wook Kim, Yongjun Park |
| 2020 | SAC | Two-tier garbage collection for persistent object. | Dokeun Lee, Youjip Won, Yongjun Park, Seongjin Lee |
| 2019 | DAC | GATE: A Generalized Dataflow-level Approximation Tuning Engine For Data Parallel Architectures. | Seokwon Kang, Yongseung Yu, Jiho Kim, Yongjun Park |
| 2018 | DATE | NN compactor: Minimizing memory and logic resources for small neural networks. | Seongmin Hong, Inho Lee, Yongjun Park |
| 2018 | SAC | Automatic code conversion for non-volatile memory. | Jinsoo Yoo, Yongjun Park, Seongjin Lee, Youjip Won |
| 2018 | Tencon | Core-level DVFS for Spatial Multitasking GPUs. | Jehee Cha, Jiho Kim, Yongjun Park |
| 2018 | Tencon | Automated Neural Network Accelerator Generation Framework for Multiple Neural Network Applications. | Inho Lee, Seongmin Hong, Giha Ryu, Yongjun Park |
| 2018 | Tencon | Runtime Profiling of OpenCL Workloads Using LLVM-based Code Instrumentation. | Yongseung Yu, Seokwon Kang, Yongjun Park |
| 2017 | ASPLOS | Dynamic Resource Management for Efficient Utilization of Multitasking GPUs. | Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke |
| 2016 | ISCA | APRES: Improving Cache Efficiency by Exploiting Load Characteristics on GPUs. | Yunho Oh, Keunsoo Kim, Myung Kuk Yoon, Jong Hyun Park, Yongjun Park, Won Woo Ro, Murali Annavaram |
| 2015 | ASPLOS | Chimera: Collaborative Preemption for Multitasking on a Shared GPU. | Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke |
| 2015 | SC | ELF: maximizing memory-level parallelism for GPUs with coordinated warp and fetch scheduling. | Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke |
| 2012 | ASPLOS | SIMD defragmenter: efficient ILP realization on data-parallel architectures. | Yongjun Park, Sangwon Seo, Hyunchul Park, Hyoun Kyu Cho, Scott A. Mahlke |
| 2012 | DAC | Process variation in near-threshold wide SIMD architectures. | Sangwon Seo, Ronald G. Dreslinski, Mark Woh, Yongjun Park, Chaitali Chakrabarti, Scott A. Mahlke, David T. Blaauw, Trevor N. Mudge |
| 2012 | MICRO | Libra: Tailoring SIMD Execution Using Heterogeneous Hardware and Dynamic Configurability. | Yongjun Park, Jason Jong Kyu Park, Hyunchul Park, Scott A. Mahlke |
| 2010 | CASES | Resource recycling: putting idle resources to work on a composable accelerator. | Yongjun Park, Hyunchul Park, Scott A. Mahlke, Sukjin Kim |
| 2009 | CASES | CGRA express: accelerating execution using dynamic operation fusion. | Yongjun Park, Hyunchul Park, Scott A. Mahlke |
| 2009 | MICRO | Polymorphic pipeline array: a flexible multicore accelerator with virtualized execution for mobile multimedia applications. | Hyunchul Park, Yongjun Park, Scott A. Mahlke |