FlashAttention-2 Varlen
Cross-source consensus on FlashAttention-2 Varlen from 1 sources and 5 claims.
1 sources · 5 claims
Uses
How it works
Comparisons
Highlighted claims
- FlashAttention-2 varlen latency stays nearly flat around 0.062 to 0.063 ms across many pruning ratios and batch sizes. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- FlashAttention-2 remains preferable for long contexts, causal masking, KV-cache usage, and compute-dominated cases. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- At ViT-scale short sequence lengths, FlashAttention-2 varlen is described as essentially all overhead at batch size 32. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- FlashAttention-2 performs better than the Triton kernel for large unpruned workloads where arithmetic dominates. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers
- FlashAttention-2 varlen is optimized for long-context language-model workloads where fixed overheads are amortized over many tokens. — Dispatch-Aware Ragged Attention for Pruned Vision Transformers