cudnn-8.0-windows10-x64-v6.0

NVIDIA® cuDNN is a GPU-accelerated library of primitives for deep neural networks. cuDNN是一个对DNN的GPU加速库。他提供高度可调整的在DNN中的常用的例程实现。 It provides highly tuned implementations of routines arising frequently in DNN applications: 常用语前向后向卷积网络，包括交叉相关。Convolution forward and backward, including cross-correlation 前像后向pooling。Pooling forward and backward 前向后向softmax。Softmax forward and backward 前向后向神经元激活。Neuron activations forward and backward Rectified linear (ReLU) Hyperbolic tangent (TANH) Tensor transformation functions LRN, LCN and batch normalization forward and backward cuDNN’s convolution routines aim for performance competitive with the fastest GEMM (matrix multiply) based implementations of such routines while using significantly less memory. cuDNN突出可定制的数据布局，支持灵活的维数排序，跨步，4D子区域for 4D张量作为输入输出。 cuDNN features customizable data layouts, supporting flexible dimension ordering, striding, and subregions for the 4D tensors used as inputs and outputs to all of its routines. This flexibility allows easy integration into any neural network implementation and avoids the input/output transposition steps sometimes necessary with GEMM-based convolutions. cuDNN offers a context-based API that allows for easy multithreading and (optional) interoperability with CUDA streams. cuDNN提供一种基于上下文的API，允许简单的多线程和CDUA流的互用。