Ragged Attention
Cross-source consensus on Ragged Attention from 1 sources and 5 claims.
1 sources · 5 claims
How it works
Preparation
Evidence quality
Where it comes from
Highlighted claims
- The ragged attention kernel implements the FlashAttention-2 online softmax algorithm specialized for bidirectional ViT inference. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- The proposed ragged attention kernel is written in Triton and is part of a three-component system with token packing and end-to-end DeiT integration. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- Ragged attention uses packed surviving tokens and cumulative sequence lengths to represent variable-length pruned batches. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- For 39 tokens per image, a single 64-by-64 tile pair covers a full image-head attention computation. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- Variable-length execution is presented as necessary for making pruning meaningful in practice, but only if dispatch overhead is low enough. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers