3 citations · 6 across the 8 of their papers we have counts for
4 papers · 1 filter
EDGC: Entropy-driven Dynamic Gradient Compression for Efficient LLM Training
Qingao Yi, Jiaang Duan, Jun Zhang +11
Training large language models (LLMs) at scale incurs substantial communication overhead, while static gradient compression cannot adapt to gradient evolution and may degrade model…
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…