Fast Gauss Sums via Flash Attention
arXiv:2609.04910v1 提出一种利用 Flash Attention 计算任意符号权重高斯核和的方法。该方法通过两次小幅度输入增强，将归一化 softmax 缩减转化为未归一化高斯求和，无需编写任何自定义 GPU 代码。在 fp16 精度及特征维度 D>8 时，此方法在速度、内存开销和准确性上均优于编译后的 PyTorch 代码及 PyKeOps 内核，且其内存缩放保持线性。
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The researchers proposed a new method based on Flash Attention technology for fast calculation of Gaussian sums. This method significantly improves the efficiency of Gaussian sum calculations by optimizing the parallel computing strategy of the attention mechanism. Experiments show that this technique demonstrates excellent performance on large-scale datasets, effectively reducing computational resource consumption and increasing processing speed.
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Fast Gauss SumsFlash AttentionPyKeOpsPyTorch
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