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Research questionHow can multi-GPU serving meet chunk-latency targets for stateful, bursty video-generation sessions?Streaming video generation keeps sessions active while producing output progressively, so the system must preserve state and repeatedly serve each session. Uneven session durations and bursts in demand make it difficult to maintain timely chunks across GPUs without wasting capacity.
AI
Inference Optimization
Technology
Video Generation
Latest papersRecent research connected to this question, newest first.TurboServe: Serving Streaming Video Generation Efficiently and EconomicallyThe source studies TurboServe for multi-GPU streaming video generation, including session placement, migration, suspension and resumption, batching, and autoscaling. Evidence comes from production traces across multiple model sizes and GPU clusters of up to 64 NVIDIA B300 GPUs; the reported latency and cost results are specific to those evaluated configurations.research paper · Jun 17, 2026
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