13 citations · 13 across the 7 of their papers we have counts for
7 papers
Accurate Simulation of Distributed Training Jobs with Network Contention Modeling
Yeonho Yoo, Hyunho Lee, Hyunmok Choi +2
Trace-driven simulation is widely used to evaluate distributed training (DT) jobs in GPU clusters, but existing simulators either ignore network contention or approximate it with a…
Residual Sparsification via Output Importance for Compressing Mixture-of-Experts LLMs
Seungwoo Jung, Dohyeok Kwon, Seungmin Cha +4
Mixture-of-experts (MoE) architectures scale large language models efficiently, but they demand massive GPU memory. To cope with such demand, models are commonly compressed to redu…
Unified KV Pooling to Accelerate Long-Context LLM Serving
Minchul Kang, Changyong Shin, Jinwoo Jeong +6
Long-context LLM serving requires offloading KV caches to host-memory and SSDs, but existing mechanisms are not designed for such long contexts. We observe significant inefficienci…
Enabling KV Caching of Shared Prefix for Diffusion Language Models
Younghun Go, Jaehoon Han, Changyong Shin +2
Key-value (KV) caching for shared prefixes is essential for high-throughput large language model (LLM) serving, but it faces critical challenges in emerging diffusion language mode…
Training Time Prediction for Mixed Precision-based Distributed Training
Minchul Kang, Changyong Shin, Jinwoo Jeong +5
Accurate prediction of training time in distributed deep learning is crucial for resource allocation, cost estimation, and job scheduling. We observe that the floating-point precis…
GPU Memory Prediction for Multimodal Model Training
Jinwoo Jeong, Minchul Kang, Younghun Go +5
As deep learning models in agentic AI systems grow in scale and complexity, GPU memory requirements increase and often exceed the available GPU memory capacity, so that out-of-memo…
Prediction of Permissioned Blockchain Performance for Resource Scaling Configurations
Seungwoo Jung, Yeonho Yoo, Gyeongsik Yang +1
Blockchain is increasingly offered as blockchain-as-a-service (BaaS) by cloud service providers. However, configuring BaaS appropriately for optimal performance and reliability res…