Hands-On Generative Adversarial Networks with Keras
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NVIDIA's CUDA Toolkit and cuDNN

NVIDIA's CUDA Toolkit provides a development environment for creating high-performance GPU-accelerated applications. You can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, workstations, enterprise data centers, cloud-based platforms, and HPC supercomputers using the CUDA Toolkit. The Toolkit includes GPU-accelerated libraries, debugging and optimization tools, a C/C++ compiler, and a runtime library to deploy your application.

Installing the CUDA Toolkit is easy and can be downloaded from https://developer.nvidia.com/cuda-downloads.

NVIDIA's cuDNN is a GPU-accelerated library of primitives for deep neural networks. cuDNN provides highly-tuned implementations for standard routines such as forward and backward convolution, pooling, normalization, and activation layers. cuDNN is part of the NVIDIA Deep Learning SDK.

cuDNN is available for members of the NVIDIA Developer Program. Registration to this program is free and members are given access to the latest NVIDIA SDKs and tools to accelerate building applications in key technology areas such as artificial intelligence, deep learning, accelerated computing, and advanced graphics (https://developer.nvidia.com/rdp/cudnn-download).

Now that we have installed NVIDIA's CUDA Toolkit and NVIDIA's cuDNN, our next step is to add environment paths.