Research
Research area:
Operating systems / File and storage systems
Parallel and distributed systems
Database systems / Blockchain systems / Big data processing
System Security
System AI / Robot & Automotive OS
< Operating Systems >
Designing and optimizing CPU scheduler for new feature
Designing and optimizing memory management for new feature
Making parallel and concurrent for OS components
Designing new data structure for OS components
< File and Storage Systems >
Making a new file system for new storage
Making efficient metadata design and data I/O operations
Designing new data structure for improving I/O performance
Optimizations for SSD and next-generation Non-volatile Memory
< Database Systems >
Designing new database components for new hardware
Making new logging and transaction systems
Improving the performance of DB backup and recovery
Designing new data structure for database components
< Parallel and Distributed Systems >
Optimizing distributed file systems
Designing new scheduler for distributed systems
Making efficient data placement and migration
Optimizing blockchain systems
< Cloud Computing, Big Data Processing, Automobile OS, Robot OS, etc >
ScaleCache: A Scalable Page Cache for Multiple Solid-State Drives
Todo
Towards HPC I/O Performance Prediction through Large-scale Log Analysis
Big data analysis of a large-scale production HPC system
Found strong correlation using various correlation analysis algorithms
Proposed a prediction scheme using machine learning approaches such as random forest and CNN
Virtual Machine Scheduling for Unreal Engine based Applications Using Google Cloud Platform (GCP) with OLIMPLANET
Streaming Service for New House Using Unreal Engine and Virtual Machine