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如何让Transformer在GPU上跑得更快?快手:需要GPU底层优化
Transformer 对计算和存储的高要求阻碍了其在 GPU 上的大规模部署。在本文中,来自快手异构计算团队的研究者分享了如何在 GPU 上实现基于 Transformer 架构的 AI 模型的极限加速,介绍了算子融合重构、混合精度量化、先进内存管理、Input Padding 移除以及 GEMM 配置等 ...
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