3 papers
cs.DC2026
ElastiCo: Elastic Configuration and Interference-Aware Orchestration for GPU Clusters
Jinghao Wang, Yihang Zhou, Xiaoyang Sun +5
Modern GPU clusters must simultaneously serve deep learning training and offline large language model inference workloads, yet existing schedulers treat these as isolated resource…
cs.DC2026
CrossPool: Efficient Multi-LLM Serving for Cold MoE Models through KV-Cache and Weight Disaggregation
Zhuoren Ye, Tianyu Wo, Dinghao Xue +4
Emerging LLM services increasingly host many sparse MoE models, yet most models receive sparse requests and remain cold. This creates a GPU memory problem: model weights are stable…
cs.DC2026
Maestro: Workload-Aware Cross-Cluster Scheduling for LLM-Based Multi-Agent Systems
Jinghao Wang, Xiao Zhou, Xiaoyang Sun +6
Large Language Model based Multi-Agent Systems (LLM-MAS) have emerged as a powerful paradigm for tackling complex tasks by breaking them into collaborative workflows of specialized…