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ORCIDSunghyun Park 0004
Person information
- affiliation: OctoAI, Seattle, WA, USA
- affiliation: University of Michigan, Ann Arbor, USA
- not to be confused with: Sunghyun Park 0006
Other persons with the same name
- Sunghyun Park (aka: SungHyun Park, Sung-Hyun Park) — disambiguation page
- Sunghyun Park 0001 — University of Southern California, Los Angeles, CA, USA
- Sunghyun Park 0002 — Massachusetts Institute of Technology, Cambridge, MA, USA
- Sunghyun Park 0003 — Samsung Electronics Co., Ltd., South Korea
- Sunghyun Park 0005
![[0009-0006-1056-2826]](https://dblp.org/img/orcid-mark.12x12.png "0009-0006-1056-2826")
— Yonsei University - Sunghyun Park 0006 — University of Michigan, Ann Arbor, USA
- Sunghyun Park 0007 — Georgia Tech, Atlanta, GA, USA
- Sunghyun Park 0008 (aka: SungHyun Park 0008) — Soongsil University, Department of Smart Systems Software, Seoul, Korea
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2020 – today
- 2025
[c11]Byungsoo Jeon, Mengdi Wu, Shiyi Cao, Sunghyun Kim, Sunghyun Park, Neeraj Aggarwal, Colin Unger, Daiyaan Arfeen, Peiyuan Liao, Xupeng Miao, Mohammad Alizadeh, Gregory R. Ganger, Tianqi Chen, Zhihao Jia:
GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. ASPLOS (1) 2025: 557-571- [c10]Ruihang Lai, Junru Shao, Siyuan Feng, Steven Lyubomirsky, Bohan Hou, Wuwei Lin, Zihao Ye, Hongyi Jin, Yuchen Jin, Jiawei Liu, Lesheng Jin, Yaxing Cai, Ziheng Jiang, Yong Wu, Sunghyun Park, Prakalp Srivastava, Jared Roesch, Todd C. Mowry, Tianqi Chen:
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning. ASPLOS (2) 2025: 998-1013 - 2024
- [i3]Byungsoo Jeon, Mengdi Wu, Shiyi Cao, Sunghyun Kim, Sunghyun Park, Neeraj Aggarwal, Colin Unger, Daiyaan Arfeen, Peiyuan Liao, Xupeng Miao, Mohammad Alizadeh, Gregory R. Ganger, Tianqi Chen, Zhihao Jia:
GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. CoRR abs/2406.17145 (2024) - 2023
- [c9]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 - [c8]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 - [i2]Ruihang Lai, Junru Shao, Siyuan Feng, Steven S. Lyubomirsky, Bohan Hou, Wuwei Lin, Zihao Ye, Hongyi Jin, Yuchen Jin, Jiawei Liu, Lesheng Jin, Yaxing Cai, Ziheng Jiang, Yong Wu, Sunghyun Park, Prakalp Srivastava, Jared G. Roesch, Todd C. Mowry, Tianqi Chen:
Relax: Composable Abstractions for End-to-End Dynamic Machine Learning. CoRR abs/2311.02103 (2023) - 2022
- [c7]Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia:
Collage: Seamless Integration of Deep Learning Backends with Automatic Placement. PACT 2022: 517-529 - [c6]Armand Behroozi, Sunghyun Park, Scott A. Mahlke:
Loner: utilizing the CPU vector datapath to process scalar integer data. CC 2022: 205-217 - [c5]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 - 2021
- [b1]Sunghyun Park:
Compiler Auto-tuning For Code Optimization. University of Michigan, USA, 2021 - [i1]Byungsoo Jeon, Sunghyun Park, Peiyuan Liao, Sheng Xu, Tianqi Chen, Zhihao Jia:
Collage: Automated Integration of Deep Learning Backends. CoRR abs/2111.00655 (2021) - 2020
- [c4]Sunghyun Park, Shikai Li, Ze Zhang, Scott A. Mahlke:
Low-cost prediction-based fault protection strategy. CGO 2020: 30-42 - [c3]Ze Zhang, Sunghyun Park, Scott A. Mahlke:
Path Sensitive Signatures for Control Flow Error Detection. LCTES 2020: 62-73
2010 – 2019
- 2019
- [j1]Sunghyun Park, Youfeng Wu, Janghaeng Lee, Amir Aupov, Scott A. Mahlke:
Multi-objective Exploration for Practical Optimization Decisions in Binary Translation. ACM Trans. Embed. Comput. Syst. 18(5s): 57:1-57:19 (2019) - 2018
- [c2]Sunghyun Park, Shikai Li, Scott A. Mahlke:
Low Cost Transient Fault Protection Using Loop Output Prediction. DSN Workshops 2018: 109-113 - [c1]Shikai Li, Sunghyun Park, Scott A. Mahlke:
Sculptor: Flexible Approximation with Selective Dynamic Loop Perforation. ICS 2018: 341-351
Coauthor Index
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