O(1) Streaming Video Prediction with GPU Memory Optimization
2025-04-19
A novel video prediction model achieves O(1) streaming complexity through optimized GPU memory layout. The model encodes input frames into GPU memory, allocating different context lengths (number of tokens) to frames based on their importance. For instance, in HunyuanVideo, a 480p frame can have its token count adjusted from 1536 to 192 using different patchifying kernels. This allows the most important frames (e.g., the one closest to the prediction target) to utilize more GPU resources, resulting in significant efficiency gains and remarkably achieving O(1) complexity without complex algorithmic optimizations.
Read more