Automated Research Spots FlashInfer Attention Kernel Bug
Posts highlight an automated research effort that located and helped resolve edge cases in FlashInfer attention kernels.
TLDR
A retweet from engineer Charles Frye shares a post by Josh Tobin describing a small win for automated research. The effort identified edge cases that could affect inference performance in FlashInfer. A linked GitHub pull request titled fix(attention): handle extreme negative logits in masked softmax details changes to the FA2 attention kernels. The PR description notes that the kernels masked logits with a finite sentinel value of math::inf = 5e4, with the online-softmax maximum tracked over the raw QK dot product. An arXiv paper on Flash Attention stability is also referenced in the visible conversation.
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