contributed by < ericlin1231 > 開發環境 $ gcc --version gcc (GCC) 14.2.1 20241116 Copyright (C) 2024 Free Software Foundation, Inc. This is free software; see the source for copying conditions. There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. $ lscpu

contributed by < ericlin1231 >

contributed by < chi0819 > Sigmoid Function by BF16 without Floating Point Support In the field of deep learning, the sigmoid function is widely used as the activation function for each layer of neural networks. Open AI project triton is a language and compiler for writing highly efficient custom Deep-Learning primitives. To write fast code at higher productivity than CUDA. triton utilize BF16 to speed up computation and more memory efficiency. For example, we can write custom GPU kernels for activation functions like the sigmoid function to accelerate computations in deep learning models output Sigmoid function maps any real-valued number to a value between 0 and 1, which makes it useful in machine learning for activating neurons in neural networks and in logistic regression for modeling probabilities $$ \sigma(x) = \frac{1}{1 + e^{-x}}

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