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ORCIDYongjun Park 0001
Person information
- affiliation: Yonsei University, Seoul, South Korea
- affiliation (former): Hanyang University, Seoul, South Korea
- affiliation (former): Hongik University, Seoul, South Korea
Other persons with the same name
- Yongjun Park 0002 — Seoul National University of Science and Technology, Seoul, South Korea
- Yongjun Park 0003 — Korea University of Technology and Education, Korea
- Yongjun Park 0004 — VisualCamp, Seoul, South Korea
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2020 – today
- 2024
[j12]Seokwon Kang
, Jongbin Kim, Gyeongyong Lee, Jeongmyung Lee, Jiwon Seo, Hyungsoo Jung, Yong Ho Song, Yongjun Park:
ISP Agent: A Generalized In-storage-processing Workload Offloading Framework by Providing Multiple Optimization Opportunities. ACM Trans. Archit. Code Optim. 21(1): 11:1-11:24 (2024)- [c44]Younghyun Lee, Hyejun Kim, Yongseung Yu, Myeongjin Cho, Jiwon Seo, Yongjun Park:
Discovering Efficient Fused Layer Configurations for Executing Multi-Workloads on Multi-Core NPUs. DATE 2024: 1-6 - [c43]Kiung Jung, Seok Namkoong, Hongjun Um, Hyejun Kim, Youngsok Kim, Yongjun Park:
Orchestrating Multiple Mixed Precision Models on a Shared Precision-Scalable NPU. LCTES 2024: 72-82 - 2023
- [j11]Deok-Jae Oh, Yaebin Moon, Do Kyu Ham, Tae Jun Ham, Yongjun Park, Jae W. Lee, Jung Ho Ahn, Eojin Lee:
MaPHeA: A Framework for Lightweight Memory Hierarchy-aware Profile-guided Heap Allocation. ACM Trans. Embed. Comput. Syst. 22(1): 2:1-2:28 (2023) - [c42]Donghyeon Kim, Taehoon Kim, Inyong Hwang, Taehyeong Park, Hanjun Kim, Youngsok Kim, Yongjun Park:
Virtual PIM: Resource-Aware Dynamic DPU Allocation and Workload Scheduling Framework for Multi-DPU PIM Architecture. PACT 2023: 112-123 - [c41]Myung-Hwan Jang, Yun-Yong Ko, Hyuck-Moo Gwon, Ikhyeon Jo, Yongjun Park, Sang-Wook Kim:
SAGE: A Storage-Based Approach for Scalable and Efficient Sparse Generalized Matrix-Matrix Multiplication. CIKM 2023: 923-933 - [c40]Seokho Lee, Younghyun Lee, Hyejun Kim, Taehoon Kim, Yongjun Park:
Block Group Scheduling: A General Precision-scalable NPU Scheduling Technique with Capacity-aware Memory Allocation. DATE 2023: 1-6 - [c39]Yongseung Yu, Donghyun Son, Younghyun Lee, Sunghyun Park, Giha Ryu, Myeongjin Cho, Jiwon Seo, Yongjun Park:
Tailoring CUTLASS GEMM using Supervised Learning. ICCD 2023: 465-474 - [c38]Taehyeong Park, Seokwon Kang, Myung-Hwan Jang, Sang-Wook Kim, Yongjun Park:
Orchestrating Large-Scale SpGEMMs using Dynamic Block Distribution and Data Transfer Minimization on Heterogeneous Systems. ICDE 2023: 2456-2459 - [c37]Beom Woo Kang, Junho Wohn, Seongju Lee, Sunghyun Park, Yung-Kyun Noh, Yongjun Park:
Synchronization-Aware NAS for an Efficient Collaborative Inference on Mobile Platforms. LCTES 2023: 13-25 - [i1]Myung-Hwan Jang, Yun-Yong Ko, Hyuck-Moo Gwon, Ikhyeon Jo, Yongjun Park, Sang-Wook Kim:
SAGE: A Storage-Based Approach for Scalable and Efficient Sparse Generalized Matrix-Matrix Multiplication. CoRR abs/2308.13626 (2023) - 2022
- [j10]Inho Lee, Yangki Lee, Hongjun Um, Seongmin Hong, Yongjun Park:
Dynamic Rate Neural Acceleration Using Multiprocessing Mode Support. IEEE Trans. Very Large Scale Integr. Syst. 30(10): 1461-1472 (2022) - [c36]Sunghyun Park, Salar Latifi, Yongjun Park, Armand Behroozi, Byungsoo Jeon, Scott A. Mahlke:
SRTuner: Effective Compiler Optimization Customization by Exposing Synergistic Relations. CGO 2022: 118-130 - [c35]Jiho Kim, Seokwon Kang, Yongjun Park, John Kim:
Networked SSD: Flash Memory Interconnection Network for High-Bandwidth SSD. MICRO 2022: 388-403 - 2021
- [c34]Kyunghwan Choi, Seongju Lee, Beom Woo Kang, Yongjun Park:
Legion: Tailoring Grouped Neural Execution Considering Heterogeneity on Multiple Edge Devices. ICCD 2021: 383-390 - [c33]Yun-Yong Ko, Jae-Seo Yu, Hong-Kyun Bae, Yongjun Park, Dongwon Lee, Sang-Wook Kim:
MASCOT: A Quantization Framework for Efficient Matrix Factorization in Recommender Systems. ICDM 2021: 290-299 - [c32]Deok-Jae Oh, Yaebin Moon, Eojin Lee, Tae Jun Ham, Yongjun Park, Jae W. Lee, Jung Ho Ahn:
MaPHeA: a lightweight memory hierarchy-aware profile-guided heap allocation framework. LCTES 2021: 24-36 - 2020
- [c31]Seokwon Kang, Kyunghwan Choi, Yongjun Park:
PreScaler: an efficient system-aware precision scaling framework on heterogeneous systems. CGO 2020: 280-292 - [c30]Jiho Kim, John Kim, Yongjun Park:
Navigator: Dynamic Multi-kernel Scheduling to Improve GPU Performance. DAC 2020: 1-6 - [c29]Hyungjun Oh, Yongseung Yu, Giha Ryu, Gunjoo Ahn, Yuri Jeong, Yongjun Park, Jiwon Seo:
Convergence-Aware Neural Network Training. DAC 2020: 1-6 - [c28]Jeongmyung Lee, Seokwon Kang, Yongseung Yu, Yong-Yeon Jo, Sang-Wook Kim, Yongjun Park:
Optimization of GPU-based Sparse Matrix Multiplication for Large Sparse Networks. ICDE 2020: 925-936 - [c27]Kyoungho Koo, Yongjun Park, Youjip Won:
LOCKED-Free Journaling: Improving the Coalescing Degree in EXT4 Journaling. NVMSA 2020: 1-6 - [c26]Dokeun Lee, Youjip Won, Yongjun Park, Seongjin Lee:
Two-tier garbage collection for persistent object. SAC 2020: 1246-1255
2010 – 2019
- 2019
- [j9]Junmo Park, Yongin Kwon, Yongjun Park, Dongsuk Jeon:
Microarchitecture-Aware Code Generation for Deep Learning on Single-ISA Heterogeneous Multi-Core Mobile Processors. IEEE Access 7: 52371-52378 (2019) - [j8]Jiho Kim, Jehee Cha, Jason Jong Kyu Park, Dongsuk Jeon, Yongjun Park:
Improving GPU Multitasking Efficiency Using Dynamic Resource Sharing. IEEE Comput. Archit. Lett. 18(1): 1-5 (2019) - [j7]Yunho Oh, Keunsoo Kim, Myung Kuk Yoon, Jong Hyun Park, Yongjun Park, Murali Annavaram, Won Woo Ro:
Adaptive Cooperation of Prefetching and Warp Scheduling on GPUs. IEEE Trans. Computers 68(4): 609-616 (2019) - [c25]Seokwon Kang, Yongseung Yu, Jiho Kim, Yongjun Park:
GATE: A Generalized Dataflow-level Approximation Tuning Engine For Data Parallel Architectures. DAC 2019: 24 - [c24]Yongseung Yu, Seokwon Kang, Yongjun Park:
A compiler-based approach for GPGPU performance calibration using TLP modulation (WIP paper). LCTES 2019: 193-197 - 2018
- [j6]Yunho Oh, Myung Kuk Yoon, Jong Hyun Park, Yongjun Park, Won Woo Ro:
WASP: Selective Data Prefetching with Monitoring Runtime Warp Progress on GPUs. IEEE Trans. Computers 67(9): 1366-1373 (2018) - [c23]Seongmin Hong, Inho Lee, Yongjun Park:
NN compactor: Minimizing memory and logic resources for small neural networks. DATE 2018: 581-584 - [c22]Jinsoo Yoo, Yongjun Park, Seongjin Lee, Youjip Won:
Automatic code conversion for non-volatile memory. SAC 2018: 1071-1076 - [c21]Yongseung Yu, Seokwon Kang, Yongjun Park:
Runtime Profiling of OpenCL Workloads Using LLVM-based Code Instrumentation. TENCON 2018: 1520-1524 - [c20]Jehee Cha, Jiho Kim, Yongjun Park:
Core-level DVFS for Spatial Multitasking GPUs. TENCON 2018: 1525-1528 - [c19]Inho Lee, Seongmin Hong, Giha Ryu, Yongjun Park:
Automated Neural Network Accelerator Generation Framework for Multiple Neural Network Applications. TENCON 2018: 2287-2290 - 2017
- [j5]Bongsuk Ko, Seunghun Han, Yongjun Park, Moongu Jeon, Byeongcheol Lee:
A Comparative Study of Programming Environments Exploiting Heterogeneous Systems. IEEE Access 5: 10081-10092 (2017) - [j4]Jiho Kim, Minsung Chu, Yongjun Park:
Efficient GPU multitasking with latency minimization and cache boosting. IEICE Electron. Express 14(7): 20161158 (2017) - [j3]Yuhwan Ro, Min Chul Sung, Yongjun Park, Jung Ho Ahn:
Selective DRAM cache bypassing for improving bandwidth on DRAM/NVM hybrid main memory systems. IEICE Electron. Express 14(11): 20170437 (2017) - [c18]Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke:
Dynamic Resource Management for Efficient Utilization of Multitasking GPUs. ASPLOS 2017: 527-540 - [c17]Seongmin Hong, Yongjun Park:
A FPGA-based neural accelerator for small IoT devices. ISOCC 2017: 294-295 - 2016
- [j2]Donghwan Jeong, Young H. Oh, Jae W. Lee, Yongjun Park:
An eDRAM-Based Approximate Register File for GPUs. IEEE Des. Test 33(1): 23-31 (2016) - [c16]Yunho Oh, Keunsoo Kim, Myung Kuk Yoon, Jong Hyun Park, Yongjun Park, Won Woo Ro, Murali Annavaram:
APRES: Improving Cache Efficiency by Exploiting Load Characteristics on GPUs. ISCA 2016: 191-203 - [c15]Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke:
A bypass first policy for energy-efficient last level caches. SAMOS 2016: 63-70 - 2015
- [j1]Janghaeng Lee, Mehrzad Samadi, Yongjun Park, Scott A. Mahlke:
SKMD: Single Kernel on Multiple Devices for Transparent CPU-GPU Collaboration. ACM Trans. Comput. Syst. 33(3): 9:1-9:27 (2015) - [c14]Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke:
Fine Grain Cache Partitioning Using Per-Instruction Working Blocks. PACT 2015: 305-316 - [c13]Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke:
Chimera: Collaborative Preemption for Multitasking on a Shared GPU. ASPLOS 2015: 593-606 - [c12]Soumyadeep Ghosh, Yongjun Park, Arun Raman:
Enabling Efficient Alias Speculation. LCTES 2015: 7:1-7:10 - [c11]Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke:
ELF: maximizing memory-level parallelism for GPUs with coordinated warp and fetch scheduling. SC 2015: 18:1-18:12 - 2013
- [c10]Janghaeng Lee, Mehrzad Samadi, Yongjun Park, Scott A. Mahlke:
Transparent CPU-GPU collaboration for data-parallel kernels on heterogeneous systems. PACT 2013: 245-255 - [c9]Jason Jong Kyu Park, Yongjun Park, Scott A. Mahlke:
Efficient execution of augmented reality applications on mobile programmable accelerators. FPT 2013: 176-183 - 2012
- [c8]Yongjun Park, Sangwon Seo, Hyunchul Park, Hyoun Kyu Cho, Scott A. Mahlke:
SIMD defragmenter: efficient ILP realization on data-parallel architectures. ASPLOS 2012: 363-374 - [c7]Sangwon Seo, Ronald G. Dreslinski, Mark Woh, Yongjun Park, Chaitali Chakrabarti, Scott A. Mahlke, David T. Blaauw, Trevor N. Mudge:
Process variation in near-threshold wide SIMD architectures. DAC 2012: 980-987 - [c6]Yongjun Park, Jason Jong Kyu Park, Scott A. Mahlke:
Efficient performance scaling of future CGRAs for mobile applications. FPT 2012: 335-342 - [c5]Yongjun Park, Jason Jong Kyu Park, Hyunchul Park, Scott A. Mahlke:
Libra: Tailoring SIMD Execution Using Heterogeneous Hardware and Dynamic Configurability. MICRO 2012: 84-95 - 2010
- [c4]Yongjun Park, Hyunchul Park, Scott A. Mahlke, Sukjin Kim:
Resource recycling: putting idle resources to work on a composable accelerator. CASES 2010: 21-30
2000 – 2009
- 2009
- [c3]Yongjun Park, Hyunchul Park, Scott A. Mahlke:
CGRA express: accelerating execution using dynamic operation fusion. CASES 2009: 271-280 - [c2]Hyunchul Park, Yongjun Park, Scott A. Mahlke:
Polymorphic pipeline array: a flexible multicore accelerator with virtualized execution for mobile multimedia applications. MICRO 2009: 370-380 - [c1]Hyunchul Park, Yongjun Park, Scott A. Mahlke:
A dataflow-centric approach to design low power control paths in CGRAs. SASP 2009: 15-20
Coauthor Index
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last updated on 2024-10-08 21:31 CEST by the dblp team
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