Compute Unified Device Architecture (CUDA) is NVIDIA’s GPU computing platform and application programming interface (API). It is designed to work with programming languages such as C, C++, and Python. CUDA can leverage GPU’s parallel computing power for various high-performance computing applications in the fields of science, healthcare, and deep learning.
The CUDA Cookbook is designed to help you learn GPU parallel programming and guide you with its modern-day application. With its help, you’ll be able to discover various CUDA programming recipes for modern GPU architectures. The book will not only guide you through GPU features, tools, and APIs, but also help you understand how to analyze performance with sample parallel programming algorithms. This useful book will ensure you gain plenty of optimization experience and insights into CUDA programming platforms with various libraries, open accelerators (OpenACC), and other languages. As you progress, you’ll even discover how to generate additional computing power with multiple GPUs in a box or multiple boxes. As you reach the concluding chapters, you’ll explore recipes on how CUDA accelerates deep learning algorithms, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs).
By the end of this book, you will be equipped with the skills you need to use the power of GPU computing in your applications.
|Course Length||15 hours 23 minutes|
|Date Of Publication||17 Jul 2019|