Sol-Attn: Accelerating Video Generation Inference via On-the-Fly Attention Sparsification

Published
Source
arXiv
Paper number
731
Field
Computer Vision
arXiv ID
2607.24027

Key points

  • It speeds up a pretrained model without training by sparsifying only the attention.
  • Block proxy scores are modeled as Gaussian, so blocks are selected using thresholds based on the mean and standard deviation.
  • It does not build a proxy-score map in memory, which reduces routing cost.
  • It reuses discarded block scores for approximate correction, so accuracy loss stays small even under aggressive sparsification.
  • It achieves end-to-end speedups of 2.1x for video generation and 2.3x for editing, without degrading quality.
  • When integrated with Sol-Engine, it reaches up to 5x acceleration for video generation.

Paper links

External research summaries. These are not HDATF publications or measured product results.

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