3 citations · 3 across the 4 of their papers we have counts for
7 papers
UCCL-EP: Portable Expert-Parallel Communication
Ziming Mao, Yihan Zhang, Chihan Cui +9
Mixture-of-Experts (MoE) workloads rely on expert parallelism (EP) to achieve high GPU efficiency. State-of-the-art EP communication systems such as DeepEP demonstrate strong perfo…
SkyNomad: On Using Multi-Region Spot Instances to Minimize AI Batch Job Cost
Zhifei Li, Tian Xia, Ziming Mao +9
AI batch jobs such as model training, inference pipelines, and data analytics require substantial GPU resources and often need to finish before a deadline. Spot instances offer 3-1…
LEANN: A Low-Storage Vector Index
Yichuan Wang, Zhifei Li, Shu Liu +10
Embedding-based vector search underpins many important applications, such as recommendation and retrieval-augmented generation (RAG). It relies on vector indices to enable efficien…
SkyWalker: A Locality-Aware Cross-Region Load Balancer for LLM Inference
Tian Xia, Ziming Mao, Jamison Kerney +5
Serving Large Language Models (LLMs) efficiently in multi-region setups remains a challenge. Due to cost and GPU availability concerns, providers typically deploy LLMs in multiple…
An Extensible Software Transport Layer for GPU Networking
Yang Zhou, Zhongjie Chen, Ziming Mao +11
Fast-evolving machine learning (ML) workloads have increasing requirements for networking. However, host network transport on RDMA NICs is hard to evolve, causing problems for ML w…
Locality-aware Fair Scheduling in LLM Serving
Shiyi Cao, Yichuan Wang, Ziming Mao +10
Large language model (LLM) inference workload dominates a wide variety of modern AI applications, ranging from multi-turn conversation to document analysis. Balancing fairness and…