4 papers
EDGC: Entropy-driven Dynamic Gradient Compression for Efficient LLM Training
Qingao Yi, Jiaang Duan, Hanwen Hu +10
Training large language models (LLMs) poses significant challenges regarding computational resources and memory capacity. Although distributed training techniques help mitigate the…
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…