2 papers
cs.DC2026
Heddle: Learning Structural Templates for Parallelism Planning on Heterogeneous GPU Clusters
Taeyoon Kim, Yonguk Song, Seoyeong Choy +4
Training large machine learning models on shared GPU infrastructures faces two challenges: (1) GPU availability shifts dynamically with varying resource demands from tenants, and (…
cs.AI2026
OrbitFlow: SLO-Aware Long-Context LLM Serving with Fine-Grained KV Cache Reconfiguration
Xinyue Ma, Heelim Hong, Taegeon Um +4
Serving long-context LLMs is challenging because request lengths and batch composition vary during token generation, causing the memory footprint to fluctuate significantly at runt…