2 citations · 2 across the 3 of their papers we have counts for
4 papers
Reliability Testing of Medical Model Performance under Distributed Deployment
Yifei Wang, Xiaohan Zhang, Youtao Ding +4
Distributed inference has become an indispensable part of deploying medical models under practical latency, memory, and throughput constraints. Although modern frameworks improve s…
Trusted Weights, Treacherous Optimizations? Optimization-Triggered Backdoor Attacks on LLMs
Yifei Wang, Tianlin Li, Xiaohan Zhang +3
Inference optimization aims to minimize the latency and resource consumption of LLM inference while preserving output quality, making large-scale deployment practical and cost-effe…
TierCheck: Tiered Checkpointing for Fault Tolerance in Large Language Model Training
Shujie Han, Feng Jiang, Patrick P. C. Lee +5
Large Language Model (LLM) training is frequently interrupted by a heterogeneous spectrum of failures, from common GPU crashes to catastrophic cluster-wide outages. Existing checkp…
Comprehensive Deadlock Prevention for GPU Collective Communication
Lichen Pan, Juncheng Liu, Yongquan Fu +4
Distributed deep neural network training necessitates efficient GPU collective communications, which are inherently susceptible to deadlocks. GPU collective deadlocks arise easily…