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arXiv:2610.02229cs.AR

Efficient FlashAttention on Blackwell via Fixed-Shift Softmax and Persistent Scheduling

Oleksandr Stashuk, Hongtao Yu, Jay Shah

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Abstract

On Blackwell, normalization and operand movement can limit attention kernels whose matrix multiplications are already deeply pipelined. We implement an FA4-style pipeline in Triton TLX with fixed-shift dense softmax and a saved inverse denominator for backward. The fixed shift removes recurrent accumulator corrections; the saved reciprocal moves row normalization from the quadratic backward loop into linear preprocessing. The guarded causal path uses a first-block anchor with selective recovery, and fully masked diagonal contractions are skipped. A packed BF16 exponential approximation and pipelined dQ publication reduce per-element work and on-chip movement. On B200 at 1,000 W, using prepared launches and the original FA4 timer, TLX improves geometric-mean throughput by 7.3 percent across the 24 cases in FA4's BF16 variable-batch grid through 32,768 tokens at head dimension 128. Dense forward and backward improve by 13.0 and 10.4 percent, respectively. Causal backward improves by 8.0 percent, while causal forward is 1.5 percent slower. The TritonBench comparison has geometric- mean gains of 13.4 percent in forward and 24.4 percent in backward

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cs.ARHardware Architecture

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