Low Cost Transient Fault Protection Using Loop Output Prediction. - Sunghyun Park 004; Shikai Li; Scott A. Mahlke (DSN Workshops, 2018)

Sculptor: Flexible Approximation with Selective Dynamic Loop Perforation. - Shikai Li; Sunghyun Park 004; Scott A. Mahlke (ICS, 2018)

Multi-objective Exploration for Practical Optimization Decisions in Binary Translation. - Sunghyun Park 004; Youfeng Wu; Janghaeng Lee; Amir Aupov; Scott A. Mahlke (ACM Trans. Embed. Comput. Syst., 2019)

Low-cost prediction-based fault protection strategy. - Sunghyun Park 004; Shikai Li; Ze Zhang; Scott A. Mahlke (CGO, 2020)

Path Sensitive Signatures for Control Flow Error Detection. - Ze Zhang; Sunghyun Park 004; Scott A. Mahlke (LCTES, 2020)

Collage: Automated Integration of Deep Learning Backends. - Byungsoo Jeon; Sunghyun Park 004; Peiyuan Liao; Sheng Xu; Tianqi Chen 001; Zhihao Jia (CoRR, 2021)

Compiler Auto-tuning For Code Optimization - Sunghyun Park 004 (2021)

Collage: Seamless Integration of Deep Learning Backends with Automatic Placement. - Byungsoo Jeon; Sunghyun Park 004; Peiyuan Liao; Sheng Xu; Tianqi Chen 001; Zhihao Jia (PACT, 2022)

Loner: utilizing the CPU vector datapath to process scalar integer data. - Armand Behroozi; Sunghyun Park 004; Scott A. Mahlke (CC, 2022)

SRTuner: Effective Compiler Optimization Customization by Exposing Synergistic Relations. - Sunghyun Park 004; Salar Latifi; Yongjun Park 001; Armand Behroozi; Byungsoo Jeon; Scott A. Mahlke (CGO, 2022)

Tailoring CUTLASS GEMM using Supervised Learning. - Yongseung Yu; Donghyun Son; Younghyun Lee; Sunghyun Park 004; Giha Ryu; Myeongjin Cho; Jiwon Seo 002; Yongjun Park 001 (ICCD, 2023)

Synchronization-Aware NAS for an Efficient Collaborative Inference on Mobile Platforms. - Beom Woo Kang; Junho Wohn; Seongju Lee; Sunghyun Park 004; Yung-Kyun Noh; Yongjun Park 001 (LCTES, 2023)

GraphPipe: Improving Performance and Scalability of DNN Training with Graph Pipeline Parallelism. - Byungsoo Jeon; Mengdi Wu; Shiyi Cao; Sunghyun Kim; Sunghyun Park 004; Neeraj Aggarwal; Colin Unger; Daiyaan Arfeen; Peiyuan Liao; Xupeng Miao; Mohammad Alizadeh; Gregory R. Ganger; et al. (ASPLOS (1), 2025)

Relax: Composable Abstractions for End-to-End Dynamic Machine Learning. - Ruihang Lai; Junru Shao; Siyuan Feng; Steven Lyubomirsky; Bohan Hou; Wuwei Lin; Zihao Ye 001; Hongyi Jin; Yuchen Jin; Jiawei Liu 004; Lesheng Jin; Yaxing Cai; et al. (ASPLOS (2), 2025)