3 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
mKernel: Fast Multi-GPU, Multi-Node Fused Kernels
Ziming Mao, Yihan Zhang, Shawn Wei Chew +5
Communication has become a bottleneck in distributed training and inference of large models. Overlapping communication with computation at the granularity of kernels, on separate s…
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…
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…