3 papers
cs.DC2026
Surviving Partial Rank Failures in Wide Expert-Parallel MoE Inference
Xun Sun, Shaoyuan Chen, Pingchuan Ma +18
Mixture-of-Experts (MoE) serving relies on wide expert parallelism (EP) to aggregate the memory capacity and bandwidth of many GPUs within one inference instance. This efficiency c…
cs.DC2026
TENT: A Declarative Slice Spraying Engine for Performant and Resilient Data Movement in Disaggregated LLM Serving
Feng Ren, Ruoyu Qin, Teng Ma +16
Modern GPU clusters rely on complex, heterogeneous interconnects. As large language model (LLM) serving shifts toward agentic reasoning, KVCache becomes a first-class mobile asset,…
cs.CV2026
StreamDiffusionV2: A Streaming System for Dynamic and Interactive Video Generation
Tianrui Feng, Zhi Li, Shuo Yang +11
Generative models are reshaping the live-streaming industry by redefining how content is created, styled, and delivered. Previous image-based streaming diffusion models have powere…