collaborators

5 papers

cs.DC2026

ITME: Inference Tiered Memory Expansion with Disaggregated CXL-Hybrid Memories

Hakbeom Jang, Younghoon Min, Sunwoong Kim +5

The rapid shift toward agentic and long-context workloads in Large Language Models (LLMs) is pushing the industry beyond the capacity of individual servers toward disaggregated sha…

cs.AI2026

Characterization of Multi-Model Agentic AI Systems on General Tasks via Trace-Driven Simulation

Donghwan Kim, Prakhar Singh, Younghoon Min +3

Agentic AI completes tasks through iterative planning, tool use, and reasoning based on observed outcomes. Despite its popularity, its system-level behavior remains poorly understo…

cs.DC2025

TraCT: Disaggregated LLM Serving with CXL Shared Memory KV Cache at Rack-Scale

Dongha Yoon, Younghoon Min, Hoshik Kim +2

Disaggregated LLM serving improves resource efficiency by separating the compute-intensive prefill phase from the latency-critical decode phase. However, this architecture introduc…

cs.DC2025

Accelerating Sparse Matrix-Matrix Multiplication on GPUs with Processing Near HBMs

Shiju Li, Younghoon Min, Hane Yie +5

Sparse General Matrix-Matrix Multiplication (SpGEMM) is a fundamental operation in numerous scientific computing and data analytics applications, often bottlenecked by irregular me…

cs.AR2025

Cocoon: A System Architecture for Differentially Private Training with Correlated Noises

Donghwan Kim, Xin Gu, Jinho Baek +6

Machine learning (ML) models memorize and leak training data, causing serious privacy issues to data owners. Training algorithms with differential privacy (DP), such as DP-SGD, hav…