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ORCIDYounghyun Cho
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2020 – today
- 2024
[j6]Almo Senja Kulinan
, Younghyun Cho, Minsoo Park, Seunghee Park:
Rapid wildfire damage estimation using integrated object-based classification with auto-generated training samples from Sentinel-2 imagery on Google Earth Engine. Int. J. Appl. Earth Obs. Geoinformation 126: 103628 (2024)- [j5]Hengrui Luo, Younghyun Cho, James Weldon Demmel, Igor Kozachenko, Xiaoye S. Li, Yang Liu:
Non-smooth Bayesian optimization in tuning scientific applications. Int. J. High Perform. Comput. Appl. 38(6): 633-657 (2024) - [c9]Changhun Lee, Jungyu Jin, Younghyun Cho, Eunhyeok Park:
QEFT: Quantization for Efficient Fine-Tuning of LLMs. EMNLP (Findings) 2024: 13823-13837 - [i4]Changhun Lee, Jungyu Jin, Younghyun Cho, Eunhyeok Park:
QEFT: Quantization for Efficient Fine-Tuning of LLMs. CoRR abs/2410.08661 (2024) - 2023
- [c8]Younghyun Cho, James Weldon Demmel, Jacob King, Xiaoye S. Li, Yang Liu, Hengrui Luo:
Harnessing the Crowd for Autotuning High-Performance Computing Applications. IPDPS 2023: 635-645 - [i3]Younghyun Cho, James Weldon Demmel, Michal Derezinski, Haoyun Li, Hengrui Luo, Michael W. Mahoney, Riley J. Murray:
Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems. CoRR abs/2308.15720 (2023) - 2022
- [c7]Younghyun Cho, Jiyeon Park, Florian Negele, Changyeon Jo, Thomas R. Gross, Bernhard Egger:
Dopia: online parallelism management for integrated CPU/GPU architectures. PPoPP 2022: 32-45 - [i2]Hengrui Luo, Younghyun Cho, James Weldon Demmel, Xiaoye S. Li, Yang Liu:
Hybrid Models for Mixed Variables in Bayesian Optimization. CoRR abs/2206.01409 (2022) - 2021
- [c6]Younghyun Cho, James Demmel, Xiaoye S. Li, Yang Liu, Hengrui Luo:
Enhancing Autotuning Capability with a History Database. MCSoC 2021: 249-257 - [i1]Hengrui Luo, James Weldon Demmel, Younghyun Cho, Xiaoye S. Li, Yang Liu:
Non-smooth Bayesian Optimization in Tuning Problems. CoRR abs/2109.07563 (2021) - 2020
- [j4]Reza Entezari-Maleki, Younghyun Cho, Bernhard Egger:
Evaluation of memory performance in NUMA architectures using Stochastic Reward Nets. J. Parallel Distributed Comput. 144: 172-188 (2020) - [j3]Younghyun Cho, Surim Oh, Bernhard Egger:
Performance Modeling of Parallel Loops on Multi-Socket Platforms Using Queueing Systems. IEEE Trans. Parallel Distributed Syst. 31(2): 318-331 (2020)
2010 – 2019
- 2018
- [c5]Younghyun Cho, Camilo A. Celis Guzman, Bernhard Egger:
Maximizing system utilization via parallelism management for co-located parallel applications. PACT 2018: 14:1-14:14 - [c4]Younghyun Cho, Florian Negele, Seohong Park, Bernhard Egger, Thomas R. Gross:
On-the-fly workload partitioning for integrated CPU/GPU architectures. PACT 2018: 21:1-21:13 - 2017
- [j2]Chung Il Jung, Yonggwan Lee, Younghyun Cho, Seongjoon Kim:
A Study of Spatial Soil Moisture Estimation Using a Multiple Linear Regression Model and MODIS Land Surface Temperature Data Corrected by Conditional Merging. Remote. Sens. 9(8): 870 (2017) - [c3]Younghyun Cho, Camilo A. Celis Guzman, Bernhard Egger:
POSTER: Improving NUMA System Efficiency with a Utilization-Based Co-scheduling. PACT 2017: 150-151 - 2016
- [j1]Bernhard Egger, Younghyun Cho, Changyeon Jo, Eunbyung Park, Jaejin Lee:
Efficient Checkpointing of Live Virtual Machines. IEEE Trans. Computers 65(10): 3041-3054 (2016) - [c2]Younghyun Cho, Surim Oh, Bernhard Egger:
Online Scalability Characterization of Data-Parallel Programs on Many Cores. PACT 2016: 191-205 - [c1]Younghyun Cho, Surim Oh, Bernhard Egger:
Adaptive Space-Shared Scheduling for Shared-Memory Parallel Programs. JSSPP 2016: 158-177
Coauthor Index
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