4 citations · 5 across the 4 of their papers we have counts for
4 papers
ReviveMoE: Fast Recovery for Hardware Failures in Large-Scale MoE LLM Inference Deployments
Haley Li, Xinglu Wang, Cong Feng +12
As LLM deployments scale over more hardware, the probability of a single failure in a system increases significantly, and cloud operators must consider robust countermeasures to ha…
HFX: Joint Design of Algorithms and Systems for Multi-SLO Serving and Fast Scaling
Zahra Yousefijamarani, Xinglu Wang, Qian Wang +12
Large language model (LLM) serving faces the dual challenge of meeting strict user-specific service-level objectives (SLOs) while minimizing computational cost under dynamic, multi…
Efficiently Serving Large Multimodal Models Using EPD Disaggregation
Gursimran Singh, Xinglu Wang, Yifan Hu +9
Large Multimodal Models (LMMs) extend Large Language Models (LLMs) by handling diverse inputs such as images, audio, and video, but at the cost of adding a multimodal encoding stag…
Artificial Intelligence for Operations Research: Revolutionizing the Operations Research Process
Zhenan Fan, Bissan Ghaddar, Xinglu Wang +3
The rapid advancement of artificial intelligence (AI) techniques has opened up new opportunities to revolutionize various fields, including operations research (OR). This survey pa…