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Together AI kernels team optimizes GPUs with FlashAttention

The Together AI kernels team, including researchers Dan Fu and Tri Dao, developed FlashAttention, a software layer that significantly optimizes GPU performance for AI models. This breakthrough, achieved by applying database system principles to GPU memory movement, resulted in 2-3x speedups, challenging the notion that transformer attention was already fully optimized. The team's subsequent work, including the ThunderKittens library, aims to accelerate kernel development for new hardware like NVIDIA's Blackwell GPUs, addressing the critical software-hardware gap in AI infrastructure. AI

IMPACT Optimizes AI inference and training by bridging the software-hardware gap, potentially lowering costs and improving responsiveness.

RANK_REASON The article details the development and impact of FlashAttention, a significant software optimization for AI workloads on GPUs, and discusses ongoing kernel research. [lever_c_demoted from research: ic=1 ai=1.0]

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COVERAGE [1]

  1. Together AI blog TIER_1 English(EN) ·

    Inside the Together AI kernels team

    The team behind FlashAttention and ThunderKittens — how Together AI's kernel researchers close the gap between GPU hardware and production AI.