ARCS

RESEARCH

Our research has focused on system-level optimizations for emerging applications such as deep learning frameworks and big data analysis platforms. Our current interests include:

• Compiler Optimization for Deep Learning Frameworks
• Optimization for Big Data Frameworks
• System Software for Emerging Non-Volatile Memory and Storage

Current Grants

• QoS Compiler for Multi-Tenant Deep Learning Applications, National Research Fund (NRF), 2025.09-2028.08
  • Explore compiler techniques to enhance Quality of Service (QoS) for deep learning applications in multi-tenant GPU environments.
• Co-design of Peta-Scale Host-Storage for Large AI Applications, Samsung Electronics, 2022.05-2026.05
  • Investigate the characteristics of big-data, deep learning applications running on specialized-SDDs and explore the design space.

[ Past Grants ]