7 papers
DABL: Detecting Semantic Anomalies in Business Processes Using Large Language Models
Wei Guan, Jian Cao, Jianqi Gao +2
Detecting anomalies in business processes is crucial for ensuring operational success. While many existing methods rely on statistical frequency to detect anomalies, it's important…
LLM-SrcLog: Towards Proactive and Unified Log Template Extraction via Large Language Models
Jiaqi Sun, Wei Li, Heng Zhang +4
Log parsing transforms raw logs into structured templates containing constants and variables. It underpins anomaly detection, failure diagnosis, and other AIOps tasks. Current pars…
GFS: A Preemption-aware Scheduling Framework for GPU Clusters with Predictive Spot Instance Management
Jiaang Duan, Shenglin Xu, Shiyou Qian +15
The surge in large language models (LLMs) has fundamentally reshaped the landscape of GPU usage patterns, creating an urgent need for more efficient management strategies. While cl…
Atys: An Efficient Profiling Framework for Identifying Hotspot Functions in Large-scale Cloud Microservices
Jiaqi Sun, Dingyu Yang, Shiyou Qian +2
To handle the high volume of requests, large-scale services are comprised of thousands of instances deployed in clouds. These services utilize diverse programming languages and are…
LKD-KGC: Domain-Specific KG Construction via LLM-driven Knowledge Dependency Parsing
Jiaqi Sun, Shiyou Qian, Zhangchi Han +5
Knowledge Graphs (KGs) structure real-world entities and their relationships into triples, enhancing machine reasoning for various tasks. While domain-specific KGs offer substantia…
LogLLM: Log-based Anomaly Detection Using Large Language Models
Wei Guan, Jian Cao, Shiyou Qian +2
Software systems often record important runtime information in logs to help with troubleshooting. Log-based anomaly detection has become a key research area that aims to identify s…