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#machine learning Preprint Sep 2026

Fast Polynomial Transcendentals for LLMs

Graphics processing unit (GPU) generations scale matrix, special-function, and memory pipelines at different rates, so kernel bottlenecks move as hardware evolves. FlashAttention-4 exposed this imbalance inside attention on NVIDIA Blackwell. We test whether short polynomial programs can accelerate other special-functio...

Robert Hu · 0 citations
#machine learning Preprint Sep 2026

Hardware-Aware FP4 FlashAttention-4

Blackwell's 4-bit floating-point (FP4) tensor cores do not automatically make attention faster because softmax conversion and on-chip dependencies dominate once its matrix products shrink. We address this with \emph{Direct-P} for noncausal inference and a causal path that passes the forward quantization directly into b...

Robert Hu · 2 citations · ⚡1

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