Online Scalability Characterization of Data-Parallel Programs on Many Cores. - Younghyun Cho; Surim Oh; Bernhard Egger 002 (PACT, 2016)

Adaptive Space-Shared Scheduling for Shared-Memory Parallel Programs. - Younghyun Cho; Surim Oh; Bernhard Egger 002 (JSSPP, 2016)

Efficient Checkpointing of Live Virtual Machines. - Bernhard Egger 002; Younghyun Cho; Changyeon Jo; Eunbyung Park; Jaejin Lee (IEEE Trans. Computers, 2016)

POSTER: Improving NUMA System Efficiency with a Utilization-Based Co-scheduling. - Younghyun Cho; Camilo A. Celis Guzman; Bernhard Egger 002 (PACT, 2017)

A Study of Spatial Soil Moisture Estimation Using a Multiple Linear Regression Model and MODIS Land Surface Temperature Data Corrected by Conditional Merging. - Chung Il Jung; Yonggwan Lee; Younghyun Cho; Seongjoon Kim (Remote. Sens., 2017)

Maximizing system utilization via parallelism management for co-located parallel applications. - Younghyun Cho; Camilo A. Celis Guzman; Bernhard Egger 002 (PACT, 2018)

On-the-fly workload partitioning for integrated CPU/GPU architectures. - Younghyun Cho; Florian Negele; Seohong Park; Bernhard Egger 002; Thomas R. Gross (PACT, 2018)

Evaluation of memory performance in NUMA architectures using Stochastic Reward Nets. - Reza Entezari-Maleki; Younghyun Cho; Bernhard Egger 002 (J. Parallel Distributed Comput., 2020)

Performance Modeling of Parallel Loops on Multi-Socket Platforms Using Queueing Systems. - Younghyun Cho; Surim Oh; Bernhard Egger 002 (IEEE Trans. Parallel Distributed Syst., 2020)

Enhancing Autotuning Capability with a History Database. - Younghyun Cho; James Demmel; Xiaoye S. Li; Yang Liu 179; Hengrui Luo (MCSoC, 2021)

Non-smooth Bayesian Optimization in Tuning Problems. - Hengrui Luo; James Weldon Demmel; Younghyun Cho; Xiaoye S. Li; Yang Liu 179 (CoRR, 2021)

Dopia: online parallelism management for integrated CPU/GPU architectures. - Younghyun Cho; Jiyeon Park; Florian Negele; Changyeon Jo; Thomas R. Gross; Bernhard Egger 002 (PPoPP, 2022)

Hybrid Models for Mixed Variables in Bayesian Optimization. - Hengrui Luo; Younghyun Cho; James Weldon Demmel; Xiaoye S. Li; Yang Liu 179 (CoRR, 2022)

Harnessing the Crowd for Autotuning High-Performance Computing Applications. - Younghyun Cho; James Weldon Demmel; Jacob King; Xiaoye S. Li; Yang Liu 179; Hengrui Luo (IPDPS, 2023)

QEFT: Quantization for Efficient Fine-Tuning of LLMs. - Changhun Lee; Jungyu Jin; Younghyun Cho; Eunhyeok Park (EMNLP (Findings), 2024)

Non-smooth Bayesian optimization in tuning scientific applications. - Hengrui Luo; Younghyun Cho; James Weldon Demmel; Igor Kozachenko; Xiaoye S. Li; Yang Liu 179 (Int. J. High Perform. Comput. Appl., 2024)

Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization. - Hengrui Luo; Younghyun Cho; James Weldon Demmel; Xiaoye S. Li; Yang Liu 179 (J. Comput. Graph. Stat., 2024)

Rapid wildfire damage estimation using integrated object-based classification with auto-generated training samples from Sentinel-2 imagery on Google Earth Engine. - Almo Senja Kulinan; Younghyun Cho; Minsoo Park; Seunghee Park (Int. J. Appl. Earth Obs. Geoinformation, 2024)

SEAL: Scaling to Emphasize Attention for Long-Context Retrieval. - Changhun Lee; Minsang Seok; Jungyu Jin; Younghyun Cho; Eunhyeok Park (ACL (1), 2025)

PTQ4VM: Post-Training Quantization for Visual Mamba. - Younghyun Cho; Changhun Lee; Seonggon Kim; Eunhyeok Park (WACV, 2025)

Surrogate-Based Autotuning for Randomized Sketching Algorithms in Regression Problems. - Younghyun Cho; James Demmel; Michal Derezinski; Haoyun Li; Hengrui Luo; Michael W. Mahoney; Riley Murray (SIAM J. Matrix Anal. Appl., 2025)

SEAL: Scaling to Emphasize Attention for Long-Context Retrieval. - Changhun Lee; Jungyu Jin; Younghyun Cho; Eunhyeok Park (CoRR, 2025)

EnQode: Fast Amplitude Embedding for Quantum Machine Learning Using Classical Data. - Jason Han; Nicholas S. DiBrita; Younghyun Cho; Hengrui Luo; Tirthak Patel (CoRR, 2025)