Kwanghyun Park

Orcid: 0000-0003-0757-2725

Affiliations:
  • Yonsei University, Seoul, South Korea
  • Microsoft Gray Systems Lab (GSL), Redmond, WA, USA (2016 - 2023)
  • University of Wisconsin-Madison, WI, USA (PhD 2016)


According to our database1, Kwanghyun Park authored at least 29 papers between 2013 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
RELOAD: A Robust and Efficient Learned Query Optimizer for Database Systems.
CoRR, April, 2026

DFLOP: A Data-driven Framework for Multimodal LLM Training Pipeline Optimization.
CoRR, March, 2026

2025
Exqutor: Extended Query Optimizer for Vector-augmented Analytical Queries.
CoRR, December, 2025

Spatial Transport Optimization by Repositioning Attention Map for Training-Free Text-to-Image Synthesis.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024
SPID-Join: A Skew-resistant Processing-in-DIMM Join Algorithm Exploiting the Bank- and Rank-level Parallelisms of DIMMs.
Proc. ACM Manag. Data, December, 2024

Trinity: In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics.
IEEE Access, 2024

Pushing ML Predictions into DBMSs (Extended Abstract).
Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023
Pushing ML Predictions Into DBMSs.
IEEE Trans. Knowl. Data Eng., October, 2023

Optimizing Data Pipelines for Machine Learning in Feature Stores.
Proc. VLDB Endow., 2023

2022
VIP Hashing - Adapting to Skew in Popularity of Data on the Fly.
Proc. VLDB Endow., 2022

Query Processing on Tensor Computation Runtimes.
Proc. VLDB Endow., 2022

VIP Hashing - Adapting to Skew in Popularity of Data on the Fly (extended version).
CoRR, 2022

End-to-end Optimization of Machine Learning Prediction Queries.
Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Trinity: End-to-End In-Database Near-Data Machine Learning Acceleration Platform for Advanced Data Analytics.
Proceedings of the 2022 IEEE Hot Chips 34 Symposium, 2022

NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching.
Proceedings of the 20th USENIX Conference on File and Storage Technologies, 2022

2021
Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads?
Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2021

FPGA for Aggregate Processing: The Good, The Bad, and The Ugly.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus.
Proceedings of the 19th USENIX Conference on File and Storage Technologies, 2021

2020
Lessons learned from the early performance evaluation of Intel optane DC persistent memory in DBMS.
Proceedings of the 16th International Workshop on Data Management on New Hardware, 2020

Extending Relational Query Processing with ML Inference.
Proceedings of the 10th Conference on Innovative Data Systems Research, 2020


2019
BlackMagic: Automatic Inlining of Scalar UDFs into SQL Queries with Froid.
Proc. VLDB Endow., 2019

Optimizing Databases by Learning Hidden Parameters of Solid State Drives.
Proc. VLDB Endow., 2019

Exploiting Intel Optane SSD for Microsoft SQL Server.
Proceedings of the 15th International Workshop on Data Management on New Hardware, 2019

2017
Froid: Optimization of Imperative Programs in a Relational Database.
Proc. VLDB Endow., 2017

Optimization of Imperative Programs in a Relational Database.
CoRR, 2017

2016
Aggressive buffer pool warm-up after restart in SQL Server.
Proceedings of the 32nd IEEE International Conference on Data Engineering Workshops, 2016

2014
Query Processing on Smart SSDs.
IEEE Data Eng. Bull., 2014

2013
Query processing on smart SSDs: opportunities and challenges.
Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013


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