8 papers
Second-Order Image Characterization with Distortion and Secrecy
Cao Daming
Image-size characterization connects coding constraints to the probability carried by source cells and their output images. At second order, this connection must retain the joint f…
DeepShare: Assurance-Driven Deep Learning Job Scheduling for Multi-Tenant Clusters
Jinghao Wang, Yihang Zhou, Xiao Zhou +5
Multi-tenant GPU clusters frequently remain underutilized even when tenants experience long queueing delays, because quota control, queue ordering, preemption, and GPU sharing are…
Latency-Aware Orchestration for Multi-Agent LLM Workflows on Heterogeneous GPUs
Jinghao Wang, Yifeng Zhang, Xiao Zhou +7
Concurrent multi-agent workflows expose future dependencies and serving-state requirements while running on heterogeneous GPU pools with time-varying load, model residency, and res…
Multi-Modal Anomaly Detection: A Survey
Xudong Mou, Zexin Wu, Chuan Luo +4
Multi-Modal Anomaly Detection (MMAD) detects rare abnormal events from heterogeneous data sources and is increasingly used in safety- and reliability-critical applications such as…
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…
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…
An Improved Time Series Anomaly Detection by Applying Structural Similarity
Tiejun Wang, Rui Wang, Xudong Mou +4
Effective anomaly detection in time series is pivotal for modern industrial applications and financial systems. Due to the scarcity of anomaly labels and the high cost of manual la…
CAPMix: Robust KPI Anomaly Detection for AIOps in Noisy and Dynamic Environments
Xudong Mou, Rui Wang, Tiejun Wang +11
Time-series anomaly detection is crucial in AIOps for maintaining large-scale service reliability. In production, streams of Key Performance Indicators (KPI) are high-dimensional,…